FIA NLS Models: Biomass vs. Stand Age, G-Reconciled – Data Subsets
JAH
2022-12-14
Background
This analysis document compliments FIA NLS Models: Biomass vs. Stand Age, G-Reconciled. All of the background information from that document applies to these analyses, which are extensions to them. The difference between that document and this analysis is the use of different data subsets.
Here, we fit the models using: 1) a temporally-balanced dataset, where we take the first and most-recent plot record for all plots in the dataset, 2) a temporally-balanced dataset (same as #1), but which excludes plot locations which have experienced harvest (at any point over the study interval 2000-2022)
Below the model fitting procedure is implemented by ecoprovince:
Analysis 1: Temporally-balanced analysis
211 - Northeastern Mixed Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 4834 1203.6
## 2 4833 1198.4 1 5.229 21.087 4.501e-06 ***
## 3 4797 1065.9 36 132.536 16.569 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 52557.62
## 2 2 52538.57
## 3 3 51686.29##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 9.371e-02 1.584e-01 0.592 0.554
## phi 2.189e-02 5.164e-03 4.238 2.3e-05 ***
## alpha 8.574e-01 3.453e-02 24.834 < 2e-16 ***
## A 4.720e+02 3.492e+01 13.516 < 2e-16 ***
## k 1.913e+02 1.634e+01 11.711 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4714 on 4797 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 8.677e-06
## (36 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Error in Mod.Sel3 %in% c(1, "1a", "1b", "1c", 4) :
## object 'Mod.Sel3' not found
## Error in Mod.Sel3 %in% c(1, "1a", "1b", "1c", 4) :
## object 'Mod.Sel3' not found
## Error in Mod.Sel3 %in% c(1, "1a", "1b", "1c", 4) :
## object 'Mod.Sel3' not found
## model AIC
## 1 3 51686.29
## 2 3a NA
## 3 3b NA
## 4 3c NA##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 9.371e-02 1.584e-01 0.592 0.554
## phi 2.189e-02 5.164e-03 4.238 2.3e-05 ***
## alpha 8.574e-01 3.453e-02 24.834 < 2e-16 ***
## A 4.720e+02 3.492e+01 13.516 < 2e-16 ***
## k 1.913e+02 1.634e+01 11.711 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4714 on 4797 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 8.677e-06
## (36 observations deleted due to missingness)summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 4832 1179.6
## 2 4831 1174.7 1 4.831 19.865 8.498e-06 ***
## 3 4795 1032.2 36 142.553 18.395 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3 51686.29
## 2 4 52463.90
## 3 5 52446.05
## 4 6 51536.04##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 2.878e-01 1.695e-01 1.697 0.0897 .
## phi 2.131e-02 5.077e-03 4.196 2.76e-05 ***
## alpha 8.507e-01 3.272e-02 26.000 < 2e-16 ***
## a 4.187e+01 1.985e+00 21.095 < 2e-16 ***
## b 1.144e+02 5.296e+00 21.609 < 2e-16 ***
## c 1.120e+02 4.466e+00 25.077 < 2e-16 ***
## d 8.929e-01 4.338e-02 20.584 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.464 on 4795 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (36 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.98555, p-value < 2.2e-16
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -28.349, p-value < 2.2e-16
## alternative hypothesis: two.sidedpredict and plot
plotting 2
212 - Laurentian Mixed Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 12943 5165.4
## 2 12940 5159.8 3 5.58 4.6656 0.002919 **
## 3 9751 3578.8 3189 1580.98 1.3508 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 135621.4
## 2 2 135589.0
## 3 3 102097.9##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.004e-01 1.380e-01 0.727 0.467
## phi 1.684e-02 4.183e-03 4.025 5.75e-05 ***
## alpha 7.029e-01 3.058e-02 22.986 < 2e-16 ***
## A 1.838e+02 7.218e+00 25.468 < 2e-16 ***
## k 6.575e+01 2.774e+00 23.697 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6058 on 9751 degrees of freedom
##
## Number of iterations to convergence: 5
## Achieved convergence tolerance: 8.023e-07
## (3206 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Error in numericDeriv(form[[3L]], names(ind), env, central = nDcentral) :
## Missing value or an infinity produced when evaluating the model
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2^s/(k^s + STDAGE_t2^s)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 9751 3578.8
## 2 9750 3513.0 1 65.778 182.56 < 2.2e-16 ***
## 3 9749 3429.0 1 84.031 238.91 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3 102097.9
## 2 3a 101918.9
## 3 3b NA
## 4 3c 101684.7##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) *
## A * STDAGE_t2^s/(k^s + STDAGE_t2^s)))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 2.104e-01 1.419e-01 1.483 0.138
## phi 1.639e-02 4.063e-03 4.035 5.51e-05 ***
## alpha 7.874e-01 2.024e-02 38.905 < 2e-16 ***
## A 1.239e+02 5.343e+00 23.190 < 2e-16 ***
## k 4.647e+01 1.612e+00 28.823 < 2e-16 ***
## p 1.969e-01 9.864e-03 19.957 < 2e-16 ***
## s 2.352e+00 1.344e-01 17.501 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5931 on 9749 degrees of freedom
##
## Number of iterations to convergence: 17
## Achieved convergence tolerance: 7.594e-06
## (3206 observations deleted due to missingness)summary
- add p model: fits
- add s model: does not fit
- add s+p model: fits
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 12941 5088.9
## 2 12938 5084.0 3 4.95 4.2015 0.005589 **
## 3 9749 3417.4 3189 1666.61 1.4909 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3c 101684.7
## 2 4 135432.3
## 3 5 135401.4
## 4 6 101651.5##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 2.376e-01 1.431e-01 1.660 0.0969 .
## phi 1.578e-02 4.052e-03 3.895 9.9e-05 ***
## alpha 7.920e-01 1.982e-02 39.963 < 2e-16 ***
## a 2.495e+01 9.866e-01 25.290 < 2e-16 ***
## b 8.618e+01 3.346e+00 25.756 < 2e-16 ***
## c 1.193e+02 5.396e+00 22.110 < 2e-16 ***
## d 1.250e+00 4.543e-02 27.525 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5921 on 9749 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (3206 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
predict and plot
plotting 2
221 - Eastern Broadleaf Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 5442 948.80
## 2 5441 948.80 1 0.00 0.0001 0.993
## 3 5404 844.42 37 104.37 18.0528 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 59550.63
## 2 2 59552.63
## 3 3 58626.28##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.841e-01 1.319e-01 1.396 0.163
## phi -3.225e-04 4.033e-03 -0.080 0.936
## alpha 8.131e-01 3.087e-02 26.339 <2e-16 ***
## A 4.751e+02 2.821e+01 16.842 <2e-16 ***
## k 1.446e+02 1.008e+01 14.350 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3953 on 5404 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 9.791e-06
## (37 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Error in numericDeriv(form[[3L]], names(ind), env, central = nDcentral) :
## Missing value or an infinity produced when evaluating the model
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 5404 844.42
## 2 5403 844.30 1 0.11944 0.7643 0.382
## model AIC
## 1 3 58626.28
## 2 3a 58627.52
## 3 3b 58613.23
## 4 3c NA##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (A * STDAGE_t2^s/(k^s +
## STDAGE_t2^s))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 2.351e-01 1.354e-01 1.737 0.0825 .
## phi -9.045e-04 4.026e-03 -0.225 0.8223
## alpha 8.196e-01 3.110e-02 26.350 < 2e-16 ***
## A 3.171e+02 2.750e+01 11.529 < 2e-16 ***
## k 7.266e+01 9.286e+00 7.825 6.05e-15 ***
## s 1.229e+00 6.088e-02 20.184 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3948 on 5403 degrees of freedom
##
## Number of iterations to convergence: 7
## Achieved convergence tolerance: 7.512e-06
## (37 observations deleted due to missingness)summary
- add p model: fits
- add s model: fits
- add s+p model: does not fit
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 5440 940.37
## 2 5439 940.37 1 0.00 0.000 1
## 3 5402 834.50 37 105.87 18.522 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3b 58613.23
## 2 4 59506.03
## 3 5 59508.03
## 4 6 58566.32##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 2.336e-01 1.346e-01 1.735 0.0828 .
## phi 0.000e+00 4.011e-03 0.000 1.0000
## alpha 8.141e-01 2.994e-02 27.186 <2e-16 ***
## a 2.993e+01 2.754e+00 10.868 <2e-16 ***
## b 1.665e+02 9.167e+00 18.167 <2e-16 ***
## c 1.428e+02 1.222e+01 11.687 <2e-16 ***
## d 1.375e+00 8.077e-02 17.026 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.393 on 5402 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (37 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
predict and plot
plotting 2
222 - Midwest Broadleaf Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 3547 1178.6
## 2 3546 1173.8 1 4.76 14.3834 0.0001516 ***
## 3 2736 837.3 810 336.54 1.3577 1.349e-08 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## model AIC
## 1 1 38157.03
## 2 2 38144.66
## 3 3 29468.73##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.49696 0.20575 -2.415 0.015785 *
## phi 0.04216 0.01152 3.660 0.000257 ***
## alpha 0.82305 0.05521 14.908 < 2e-16 ***
## A 510.07403 59.25009 8.609 < 2e-16 ***
## k 204.81027 26.87562 7.621 3.46e-14 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5532 on 2736 degrees of freedom
##
## Number of iterations to convergence: 7
## Achieved convergence tolerance: 4.721e-06
## (811 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Error in numericDeriv(form[[3L]], names(ind), env, central = nDcentral) :
## Missing value or an infinity produced when evaluating the model
## Error in numericDeriv(form[[3L]], names(ind), env, central = nDcentral) :
## Missing value or an infinity produced when evaluating the model
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 2736 837.30
## 2 2735 836.95 1 0.345 1.1274 0.2884
## model AIC
## 1 3 29468.73
## 2 3a 29469.60
## 3 3b NA
## 4 3c NA##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.49696 0.20575 -2.415 0.015785 *
## phi 0.04216 0.01152 3.660 0.000257 ***
## alpha 0.82305 0.05521 14.908 < 2e-16 ***
## A 510.07403 59.25009 8.609 < 2e-16 ***
## k 204.81027 26.87562 7.621 3.46e-14 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5532 on 2736 degrees of freedom
##
## Number of iterations to convergence: 7
## Achieved convergence tolerance: 4.721e-06
## (811 observations deleted due to missingness)summary
- add p model: fits
- add s model: does not fit
- add s+p model: does not fit
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 3545 1160.08
## 2 3544 1155.44 1 4.64 14.2326 0.0001642 ***
## 3 2734 811.87 810 343.57 1.4284 3.814e-11 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3 29468.73
## 2 4 38104.80
## 3 5 38092.57
## 4 6 29388.21##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.39139 0.21414 -1.828 0.067694 .
## phi 0.04407 0.01139 3.870 0.000111 ***
## alpha 0.84560 0.04743 17.827 < 2e-16 ***
## a 28.12536 2.22465 12.643 < 2e-16 ***
## b 125.18955 7.61599 16.438 < 2e-16 ***
## c 104.14395 6.01856 17.304 < 2e-16 ***
## d 1.01334 0.06134 16.520 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5449 on 2734 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (811 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.95927, p-value < 2.2e-16
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -17.002, p-value < 2.2e-16
## alternative hypothesis: two.sidedpredict and plot
plotting 2
223 - Central Interior Broadleaf Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 6383 1208.62
## 2 6382 1205.07 1 3.549 18.7934 1.479e-05 ***
## 3 5253 959.89 1129 245.185 1.1885 7.222e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 66739.63
## 2 2 66722.85
## 3 3 54960.87##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.076148 0.122692 -0.621 0.53486
## phi -0.017140 0.005541 -3.093 0.00199 **
## alpha 0.752631 0.033877 22.217 < 2e-16 ***
## A 274.803374 12.815771 21.443 < 2e-16 ***
## k 76.174549 4.734840 16.088 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4275 on 5253 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 5.076e-07
## (1130 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Error in numericDeriv(form[[3L]], names(ind), env, central = nDcentral) :
## Missing value or an infinity produced when evaluating the model
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 5253 959.89
## 2 5252 959.83 1 0.055076 0.3014 0.5831
## model AIC
## 1 3 54960.87
## 2 3a 54962.57
## 3 3b 54936.56
## 4 3c NA##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (A * STDAGE_t2^s/(k^s +
## STDAGE_t2^s))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.046206 0.124285 -0.372 0.71007
## phi -0.017210 0.005522 -3.117 0.00184 **
## alpha 0.761109 0.034070 22.340 < 2e-16 ***
## A 192.955583 11.041778 17.475 < 2e-16 ***
## k 40.235430 3.159348 12.735 < 2e-16 ***
## s 1.392459 0.078233 17.799 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4264 on 5252 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 4.199e-06
## (1130 observations deleted due to missingness)summary
- add p model: fits
- add s model: fits
- add s+p model: does not fit
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 6381 1195.86
## 2 6380 1195.86 1 0.00 0.0000 1
## 3 5251 944.25 1129 251.61 1.2393 1.062e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3b 54936.56
## 2 4 66675.81
## 3 5 66677.81
## 4 6 54878.47##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.19990 0.11554 -1.73 0.0837 .
## phi 0.00000 0.00566 0.00 1.0000
## alpha 0.76139 0.03295 23.11 <2e-16 ***
## a 31.44045 2.91648 10.78 <2e-16 ***
## b 117.40902 5.20293 22.57 <2e-16 ***
## c 106.43496 6.07343 17.52 <2e-16 ***
## d 1.26371 0.07424 17.02 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4241 on 5251 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (1130 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
predict and plot
plotting 2
231 - Southeastern Mixed Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 7773 2698.5
## 2 7772 2698.1 1 0.388 1.1185 0.2903
## 3 7640 2402.6 132 295.453 7.1174 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 85845.56
## 2 2 85846.44
## 3 3 84005.02##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.306518 0.177137 7.376 1.81e-13 ***
## phi -0.005339 0.004923 -1.084 0.278
## alpha 0.615720 0.024140 25.506 < 2e-16 ***
## A 223.187781 9.171669 24.334 < 2e-16 ***
## k 51.702124 2.145762 24.095 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5608 on 7640 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 2.623e-06
## (145 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Error in nls(get(paste("f_", Mod.Sel1, "b", sep = "")), data = G_231, :
## number of iterations exceeded maximum of 50
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2^s/(k^s + STDAGE_t2^s)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 7640 2402.6
## 2 7639 2305.2 1 97.44 322.90 < 2.2e-16 ***
## 3 7638 2248.0 1 57.17 194.24 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3 84005.02
## 2 3a 83690.51
## 3 3b NA
## 4 3c 83500.52##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) *
## A * STDAGE_t2^s/(k^s + STDAGE_t2^s)))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 2.049414 0.216854 9.451 <2e-16 ***
## phi -0.007112 0.004685 -1.518 0.129
## alpha 0.780893 0.015254 51.193 <2e-16 ***
## A 131.000889 5.856863 22.367 <2e-16 ***
## k 32.455981 1.180812 27.486 <2e-16 ***
## p 0.186722 0.009448 19.763 <2e-16 ***
## s 2.290107 0.127126 18.014 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5425 on 7638 degrees of freedom
##
## Number of iterations to convergence: 15
## Achieved convergence tolerance: 7.348e-06
## (145 observations deleted due to missingness)summary
- add p model: fits
- add s model: does not fit
- add s+p model: fits
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 7771 2669.8
## 2 7770 2669.8 1 0.00 0.000 1
## 3 7638 2247.0 132 422.83 10.889 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3c 83500.52
## 2 4 85766.57
## 3 5 85768.57
## 4 6 83497.02##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.903e+00 2.074e-01 9.177 <2e-16 ***
## phi 0.000e+00 4.679e-03 0.000 1
## alpha 7.803e-01 1.524e-02 51.210 <2e-16 ***
## a 2.529e+01 9.630e-01 26.263 <2e-16 ***
## b 1.027e+02 5.028e+00 20.418 <2e-16 ***
## c 1.055e+02 7.798e+00 13.523 <2e-16 ***
## d 1.434e+00 6.274e-02 22.859 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5424 on 7638 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (145 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
predict and plot
plotting 2
232 - Outer Coastal Plain Mixed Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 7905 4072.2
## 2 7904 4066.6 1 5.58 10.845 0.0009948 ***
## 3 7734 3731.9 170 334.69 4.080 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 88878.43
## 2 2 88869.59
## 3 3 86866.19##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 7.250e-01 1.821e-01 3.981 6.91e-05 ***
## phi 1.443e-02 5.585e-03 2.584 0.00978 **
## alpha 6.107e-01 2.691e-02 22.695 < 2e-16 ***
## A 2.312e+02 1.127e+01 20.522 < 2e-16 ***
## k 5.172e+01 2.622e+00 19.725 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6946 on 7734 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 4.112e-06
## (201 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Error in nls(get(paste("f_", Mod.Sel1, "b", sep = "")), data = G_232, :
## number of iterations exceeded maximum of 50
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2^s/(k^s + STDAGE_t2^s)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 7734 3731.9
## 2 7733 3561.2 1 170.777 370.84 < 2.2e-16 ***
## 3 7732 3486.0 1 75.186 166.77 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3 86866.19
## 2 3a 86505.68
## 3 3b NA
## 4 3c 86342.54##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) *
## A * STDAGE_t2^s/(k^s + STDAGE_t2^s)))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.180e+00 2.037e-01 5.796 7.06e-09 ***
## phi 1.951e-02 5.268e-03 3.704 0.000214 ***
## alpha 8.157e-01 1.491e-02 54.709 < 2e-16 ***
## A 1.435e+02 7.160e+00 20.040 < 2e-16 ***
## k 3.445e+01 1.453e+00 23.704 < 2e-16 ***
## p 2.051e-01 1.124e-02 18.249 < 2e-16 ***
## s 2.380e+00 1.583e-01 15.031 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6715 on 7732 degrees of freedom
##
## Number of iterations to convergence: 30
## Achieved convergence tolerance: 8.441e-06
## (201 observations deleted due to missingness)summary
- add p model: fits
- add s model: does not fit
- add s+p model: fits
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 7903 4029.5
## 2 7902 4023.0 1 6.53 12.8240 0.0003443 ***
## 3 7732 3483.8 170 539.18 7.0391 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3c 86342.54
## 2 4 88799.14
## 3 5 88788.32
## 4 6 86337.79##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.150e+00 2.016e-01 5.703 1.22e-08 ***
## phi 1.931e-02 5.265e-03 3.668 0.000246 ***
## alpha 8.152e-01 1.490e-02 54.722 < 2e-16 ***
## a 2.973e+01 1.259e+00 23.612 < 2e-16 ***
## b 1.110e+02 6.334e+00 17.530 < 2e-16 ***
## c 1.133e+02 1.013e+01 11.182 < 2e-16 ***
## d 1.416e+00 7.419e-02 19.085 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6712 on 7732 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (201 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
predict and plot
plotting 2
234 - Lower Mississippi Riverine Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 826 218.04
## 2 825 217.18 1 0.858 3.2587 0.07141 .
## 3 796 176.62 29 40.558 6.3031 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 9094.121
## 2 2 9092.853
## 3 3 8721.076##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.03331 0.42869 -0.078 0.938079
## phi 0.02377 0.01704 1.395 0.163503
## alpha 0.78853 0.06572 11.998 < 2e-16 ***
## A 773.16127 194.86026 3.968 7.91e-05 ***
## k 245.90341 70.09441 3.508 0.000477 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.471 on 796 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 2.03e-06
## (29 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Error in numericDeriv(form[[3L]], names(ind), env, central = nDcentral) :
## Missing value or an infinity produced when evaluating the model
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 796 176.62
## 2 795 176.57 1 0.053697 0.2418 0.6231
## model AIC
## 1 3 8721.076
## 2 3a 8722.832
## 3 3b 8722.697
## 4 3c NA##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.03331 0.42869 -0.078 0.938079
## phi 0.02377 0.01704 1.395 0.163503
## alpha 0.78853 0.06572 11.998 < 2e-16 ***
## A 773.16127 194.86026 3.968 7.91e-05 ***
## k 245.90341 70.09441 3.508 0.000477 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.471 on 796 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 2.03e-06
## (29 observations deleted due to missingness)summary
- add p model: fits
- add s model: fits
- add s+p model: does not fit
model selection 3
## Error in nls(f_5, data = G_234, start = c(ge = ge.start, phi = phi.start, :
## Convergence failure: singular convergence (7)
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 824 216.69
## 2 794 176.36 30 40.328 6.0523 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3 8721.076
## 2 4 9092.966
## 3 5 NA
## 4 6 8723.879##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.03331 0.42869 -0.078 0.938079
## phi 0.02377 0.01704 1.395 0.163503
## alpha 0.78853 0.06572 11.998 < 2e-16 ***
## A 773.16127 194.86026 3.968 7.91e-05 ***
## k 245.90341 70.09441 3.508 0.000477 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.471 on 796 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 2.03e-06
## (29 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: does not fit
- log-normal phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.9564, p-value = 1.117e-14
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -10.183, p-value < 2.2e-16
## alternative hypothesis: two.sidedpredict and plot
plotting 2
242 - Pacific Lowland Mixed Forest
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
## [1] "cannot plot observed vs. predicted"251 - Prairie Parkland (Temperate)
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 1387 347.56
## 2 1386 347.55 1 0.009 0.0358 0.85
## 3 976 201.22 410 146.336 1.7312 4.576e-12 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 14526.30
## 2 2 14528.27
## 3 3 10148.74##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.72569 0.45999 1.578 0.115
## phi -0.01189 0.01093 -1.087 0.277
## alpha 0.74240 0.08614 8.618 < 2e-16 ***
## A 233.44634 31.56045 7.397 3.0e-13 ***
## k 97.74632 14.64004 6.677 4.1e-11 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4541 on 976 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 5.34e-06
## (411 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Error in numericDeriv(form[[3L]], names(ind), env, central = nDcentral) :
## Missing value or an infinity produced when evaluating the model
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 976 201.22
## 2 975 199.45 1 1.7642 8.6238 0.003396 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3 10148.74
## 2 3a 10142.10
## 3 3b 10132.44
## 4 3c NA##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (A * STDAGE_t2^s/(k^s +
## STDAGE_t2^s))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.675553 0.446554 1.513 0.131
## phi -0.009984 0.010881 -0.917 0.359
## alpha 0.758099 0.086092 8.806 < 2e-16 ***
## A 131.142574 15.123500 8.671 < 2e-16 ***
## k 36.877878 3.369293 10.945 < 2e-16 ***
## s 1.907117 0.235354 8.103 1.59e-15 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4501 on 975 degrees of freedom
##
## Number of iterations to convergence: 7
## Achieved convergence tolerance: 1.167e-06
## (411 observations deleted due to missingness)summary
- add p model: fits
- add s model: fits
- add s+p model: does not fit
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 1385 337.23
## 2 1384 337.21 1 0.028 0.1133 0.7364
## 3 974 196.75 410 140.452 1.6958 2.805e-11 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3b 10132.44
## 2 4 14488.37
## 3 5 14490.26
## 4 6 10130.73##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.52834 0.42228 1.251 0.21117
## phi 0.00000 0.01109 0.000 1.00000
## alpha 0.75256 0.08644 8.706 < 2e-16 ***
## a 20.68200 7.89781 2.619 0.00896 **
## b 94.56775 12.14165 7.789 1.73e-14 ***
## c 104.72342 10.87647 9.628 < 2e-16 ***
## d 1.19567 0.16622 7.193 1.26e-12 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4495 on 974 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (411 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.97083, p-value = 3.951e-13
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -7.8579, p-value = 3.907e-15
## alternative hypothesis: two.sidedpredict and plot
plotting 2
255 - Prairie Parkland (Subtropical)
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 439 237.09
## 2 438 236.77 1 0.320 0.5915 0.4423
## 3 414 203.61 24 33.163 2.8095 1.648e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 4609.958
## 2 2 4611.362
## 3 3 4398.952##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.06044 0.57866 -0.104 0.917
## phi -0.01117 0.02199 -0.508 0.612
## alpha 0.52728 0.13377 3.942 9.49e-05 ***
## A 168.90330 33.06689 5.108 4.98e-07 ***
## k 48.88934 11.19265 4.368 1.59e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7013 on 414 degrees of freedom
##
## Number of iterations to convergence: 5
## Achieved convergence tolerance: 4.307e-06
## (25 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Error in nls(get(paste("f_", Mod.Sel1, "b", sep = "")), data = G_255, :
## number of iterations exceeded maximum of 50
## Error in numericDeriv(form[[3L]], names(ind), env, central = nDcentral) :
## Missing value or an infinity produced when evaluating the model
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 414 203.61
## 2 413 195.02 1 8.5942 18.201 2.468e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3 4398.952
## 2 3a 4382.882
## 3 3b NA
## 4 3c NA##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) *
## A * STDAGE_t2/(k + STDAGE_t2)))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.20658 0.63441 0.326 0.7449
## phi -0.01148 0.02110 -0.544 0.5866
## alpha 0.65556 0.09706 6.754 4.89e-11 ***
## A 350.53518 253.12950 1.385 0.1669
## k 210.79807 205.12582 1.028 0.3047
## p 0.04281 0.02445 1.751 0.0806 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6872 on 413 degrees of freedom
##
## Number of iterations to convergence: 18
## Achieved convergence tolerance: 8.782e-06
## (25 observations deleted due to missingness)summary
- add p model: fits
- add s model: does not fit
- add s+p model: does not fit
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 437 226.64
## 2 436 226.38 1 0.257 0.495 0.4821
## 3 412 182.67 24 43.713 4.108 1.104e-09 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3a 4382.882
## 2 4 4594.028
## 3 5 4595.526
## 4 6 4357.477##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.12210 0.58498 0.209 0.835
## phi 0.00000 0.02007 0.000 1.000
## alpha 0.72207 0.08300 8.700 < 2e-16 ***
## a 24.95845 3.47809 7.176 3.37e-12 ***
## b 67.55150 9.97122 6.775 4.32e-11 ***
## c 54.80781 4.97573 11.015 < 2e-16 ***
## d 0.85562 0.11805 7.248 2.10e-12 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6659 on 412 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (25 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.94119, p-value = 7.977e-12
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -4.1487, p-value = 3.344e-05
## alternative hypothesis: two.sidedpredict and plot
plotting 2
261 - California Coastal Chaparral Forest and Shrub
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
add p model: does not fit
add s model: does not fit
add s+p model: does not fit
unable to fit model (only 64 observations)
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
## [1] "cannot plot observed vs. predicted"262 - California Dry Steppe
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
add p model: does not fit
add s model: does not fit
add s+p model: does not fit
unable to fit model (0 observations)
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
## [1] "cannot plot observed vs. predicted"263 - California Coastal Steppe - Mixed Forest and Redwood Forest
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
## [1] "cannot plot observed vs. predicted"313 - Colorado Plateau Semi-Desert
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
## [1] "cannot plot observed vs. predicted"315 - Southwest Plateau and Plains Dry Steppe and Shrub
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
## [1] "cannot plot observed vs. predicted"321 - Chihuahuan Semi-Desert
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
## [1] "cannot plot observed vs. predicted"322 - American Semidesert and Desert
model selection 1
## Error in if (any(nEQ <- vNms != make.names(vNms))) vNms[nEQ] <- paste0("`", :
## missing value where TRUE/FALSE needed## Error in if (any(nEQ <- vNms != make.names(vNms))) vNms[nEQ] <- paste0("`", :
## missing value where TRUE/FALSE needed## Error in if (any(nEQ <- vNms != make.names(vNms))) vNms[nEQ] <- paste0("`", :
## missing value where TRUE/FALSE needed## model AIC
## 1 1 NA
## 2 2 NA
## 3 3 NA## Warning in min(AIC1_322$AIC, na.rm = T): no non-missing arguments to min;
## returning Inf## Error in get(paste("nls_322.", Mod.Sel1, sep = "")) :
## object 'nls_322.' not foundsummary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
## [1] "cannot plot observed vs. predicted"- Cannot fit model
- not enough data (only 3 observations)
331 - Great Plains/Palouse Dry Steppe
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
## [1] "cannot plot observed vs. predicted"- Cannot fit model
332 - Great Plains Steppe
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 149 87.775
## 2 148 87.770 1 0.0054 0.0091 0.9243
## 3 134 78.060 14 9.7102 1.1906 0.2895
## model AIC
## 1 1 1640.707
## 2 2 1642.698
## 3 3 1513.662##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.26596 2.70800 0.467 0.640911
## phi 0.02123 0.04175 0.509 0.611881
## alpha 1.02394 0.28761 3.560 0.000513 ***
## A 172.21708 111.72522 1.541 0.125569
## k 97.50664 66.42911 1.468 0.144494
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7632 on 134 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 5.907e-06
## (15 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Error in nls(get(paste("f_", Mod.Sel1, "a", sep = "")), data = G_332, :
## number of iterations exceeded maximum of 50
## Error in nls(get(paste("f_", Mod.Sel1, "b", sep = "")), data = G_332, :
## number of iterations exceeded maximum of 50
## Error in numericDeriv(form[[3L]], names(ind), env, central = nDcentral) :
## Missing value or an infinity produced when evaluating the model
## model AIC
## 1 3 1513.662
## 2 3a NA
## 3 3b NA
## 4 3c NA##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.26596 2.70800 0.467 0.640911
## phi 0.02123 0.04175 0.509 0.611881
## alpha 1.02394 0.28761 3.560 0.000513 ***
## A 172.21708 111.72522 1.541 0.125569
## k 97.50664 66.42911 1.468 0.144494
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7632 on 134 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 5.907e-06
## (15 observations deleted due to missingness)summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 147 83.369
## 2 146 83.369 1 0.000 0.0000 1.0000
## 3 132 72.682 14 10.688 1.3864 0.1682
## model AIC
## 1 3 1513.662
## 2 4 1636.879
## 3 5 1638.879
## 4 6 1507.740##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 2.229e+00 3.519e+00 0.634 0.527422
## phi 4.601e-03 3.909e-02 0.118 0.906483
## alpha 1.034e+00 2.781e-01 3.718 0.000296 ***
## a 2.383e+01 1.470e+01 1.621 0.107315
## b 5.124e+01 3.508e+01 1.461 0.146476
## c 1.160e+02 9.460e+01 1.227 0.222165
## d 1.069e+00 7.322e-01 1.461 0.146518
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.742 on 132 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (15 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.87905, p-value = 2.876e-09
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -3.5188, p-value = 0.0004335
## alternative hypothesis: two.sidedpredict and plot
plotting 2
341 - Nevada-Utah Mountains Semi-Desert - Coniferous Forest - Alpine Meadow
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"- model not fitted because only 62 observations
predict and plot
## [1] "cannot plot data with prediction"plotting 2
## [1] "cannot plot observed vs. predicted"342 - Intermountain Semi-Desert
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
## [1] "cannot plot observed vs. predicted"411 - Everglades
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
## [1] "cannot plot observed vs. predicted"M211 - Adirondack-New England Mixed forest - Coniferous Forest - Alpine Meadow
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 5103 963.25
## 2 5102 953.15 1 10.106 54.096 2.213e-13 ***
## 3 5087 816.07 15 137.075 56.964 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 54262.24
## 2 2 54210.39
## 3 3 53319.17##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.45428 0.15363 2.957 0.00312 **
## phi 0.02721 0.00411 6.620 3.95e-11 ***
## alpha 0.80377 0.02644 30.401 < 2e-16 ***
## A 412.15962 25.00388 16.484 < 2e-16 ***
## k 176.59637 11.52461 15.323 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4005 on 5087 degrees of freedom
##
## Number of iterations to convergence: 7
## Achieved convergence tolerance: 1.867e-06
## (16 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Error in numericDeriv(form[[3L]], names(ind), env, central = nDcentral) :
## Missing value or an infinity produced when evaluating the model
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 5087 816.07
## 2 5086 812.13 1 3.9424 24.689 6.957e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3 53319.17
## 2 3a 53296.51
## 3 3b 53279.84
## 4 3c NA##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (A * STDAGE_t2^s/(k^s +
## STDAGE_t2^s))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 3.801e-01 1.484e-01 2.561 0.0105 *
## phi 2.507e-02 4.077e-03 6.148 8.42e-10 ***
## alpha 8.123e-01 2.661e-02 30.529 < 2e-16 ***
## A 2.419e+02 1.643e+01 14.722 < 2e-16 ***
## k 6.902e+01 6.668e+00 10.352 < 2e-16 ***
## s 1.320e+00 5.481e-02 24.079 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3989 on 5086 degrees of freedom
##
## Number of iterations to convergence: 8
## Achieved convergence tolerance: 4.448e-06
## (16 observations deleted due to missingness)summary
- add p model: fits
- add s model: fits
- add s+p model: does not fit
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 5101 952.58
## 2 5100 943.77 1 8.811 47.612 5.829e-12 ***
## 3 5085 806.69 15 137.078 57.605 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3b 53279.84
## 2 4 54209.36
## 3 5 54163.91
## 4 6 53264.31##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 4.171e-01 1.510e-01 2.763 0.00575 **
## phi 2.471e-02 4.066e-03 6.078 1.31e-09 ***
## alpha 8.146e-01 2.613e-02 31.172 < 2e-16 ***
## a 1.948e+01 2.829e+00 6.886 6.45e-12 ***
## b 1.479e+02 9.524e+00 15.526 < 2e-16 ***
## c 1.749e+02 1.851e+01 9.447 < 2e-16 ***
## d 1.523e+00 1.005e-01 15.155 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3983 on 5085 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (16 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
predict and plot
plotting 2
M221 - Eastern Broadleaf Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 5180 879.40
## 2 5179 872.62 1 6.779 40.231 2.448e-10 ***
## 3 5151 806.45 28 66.178 15.096 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 57351.18
## 2 2 57313.08
## 3 3 56678.87##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.063850 0.161829 6.574 5.39e-11 ***
## phi -0.030024 0.004525 -6.635 3.58e-11 ***
## alpha 0.828797 0.041483 19.979 < 2e-16 ***
## A 244.905969 9.585367 25.550 < 2e-16 ***
## k 57.563428 2.889563 19.921 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3957 on 5151 degrees of freedom
##
## Number of iterations to convergence: 5
## Achieved convergence tolerance: 4.999e-06
## (30 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (A * STDAGE_t2^s/(k^s + STDAGE_t2^s))
## Model 4: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2^s/(k^s + STDAGE_t2^s)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 5151 806.45
## 2 5150 806.45 1 0.0005 0.0034 0.9535
## 3 5150 802.47 0 0.0000
## 4 5149 783.02 1 19.4478 127.8852 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3 56678.87
## 2 3a 56680.87
## 3 3b 56655.37
## 4 3c 56530.88##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) *
## A * STDAGE_t2^s/(k^s + STDAGE_t2^s)))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.26879 0.17208 7.373 1.93e-13 ***
## phi -0.03036 0.00444 -6.838 8.96e-12 ***
## alpha 0.83333 0.03778 22.056 < 2e-16 ***
## A 150.83652 5.37184 28.079 < 2e-16 ***
## k 38.54357 1.02378 37.648 < 2e-16 ***
## p 0.26168 0.01751 14.944 < 2e-16 ***
## s 3.02312 0.23227 13.016 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.39 on 5149 degrees of freedom
##
## Number of iterations to convergence: 10
## Achieved convergence tolerance: 3.986e-06
## (30 observations deleted due to missingness)summary
- add p model: fits
- add s model: fits
- add s+p model: fits
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 5178 862.65
## 2 5177 862.65 1 0.000 0.000 1
## 3 5149 789.00 28 73.645 17.164 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3c 56530.88
## 2 4 57255.49
## 3 5 57257.49
## 4 6 56570.14##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) *
## A * STDAGE_t2^s/(k^s + STDAGE_t2^s)))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.26879 0.17208 7.373 1.93e-13 ***
## phi -0.03036 0.00444 -6.838 8.96e-12 ***
## alpha 0.83333 0.03778 22.056 < 2e-16 ***
## A 150.83652 5.37184 28.079 < 2e-16 ***
## k 38.54357 1.02378 37.648 < 2e-16 ***
## p 0.26168 0.01751 14.944 < 2e-16 ***
## s 3.02312 0.23227 13.016 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.39 on 5149 degrees of freedom
##
## Number of iterations to convergence: 10
## Achieved convergence tolerance: 3.986e-06
## (30 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
predict and plot
plotting 2
M223 - Ozark Broadleaf Forest Meadow
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 596 80.866
## 2 595 78.165 1 2.7013 20.563 6.981e-06 ***
## 3 593 69.832 2 8.3328 35.381 3.049e-15 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 6115.535
## 2 2 6097.184
## 3 3 6024.464##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.65199 0.22705 -2.872 0.004231 **
## phi 0.06644 0.01727 3.847 0.000133 ***
## alpha 0.87209 0.09746 8.948 < 2e-16 ***
## A 328.23839 44.23555 7.420 4.07e-13 ***
## k 95.23106 18.35173 5.189 2.90e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3432 on 593 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 1.679e-06
## (4 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Error in nls(get(paste("f_", Mod.Sel1, "c", sep = "")), data = G_M223, :
## number of iterations exceeded maximum of 50
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 593 69.832
## 2 592 69.732 1 0.099537 0.845 0.3583
## model AIC
## 1 3 6024.464
## 2 3a 6025.611
## 3 3b 6026.057
## 4 3c NA##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.65199 0.22705 -2.872 0.004231 **
## phi 0.06644 0.01727 3.847 0.000133 ***
## alpha 0.87209 0.09746 8.948 < 2e-16 ***
## A 328.23839 44.23555 7.420 4.07e-13 ***
## k 95.23106 18.35173 5.189 2.90e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3432 on 593 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 1.679e-06
## (4 observations deleted due to missingness)summary
- add p model: fits
- add s model: fits
- add s+p model: does not fit
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 594 80.723
## 2 593 78.002 1 2.7205 20.682 6.577e-06 ***
## 3 591 69.748 2 8.2546 34.972 4.419e-15 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3 6024.464
## 2 4 6118.473
## 3 5 6099.938
## 4 6 6027.743##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.65199 0.22705 -2.872 0.004231 **
## phi 0.06644 0.01727 3.847 0.000133 ***
## alpha 0.87209 0.09746 8.948 < 2e-16 ***
## A 328.23839 44.23555 7.420 4.07e-13 ***
## k 95.23106 18.35173 5.189 2.90e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3432 on 593 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 1.679e-06
## (4 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.96799, p-value = 3.877e-10
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -8.2615, p-value < 2.2e-16
## alternative hypothesis: two.sidedpredict and plot
plotting 2
M231 - Ouachita Mixed Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 676 152.77
## 2 675 152.74 1 0.0331 0.1463 0.7022
## 3 668 137.45 7 15.2872 10.6137 1.062e-12 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 7025.553
## 2 2 7027.406
## 3 3 6914.896##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.88582 0.65606 1.350 0.177
## phi -0.01472 0.01648 -0.893 0.372
## alpha 0.88301 0.11088 7.964 7.21e-15 ***
## A 271.33123 53.95943 5.028 6.36e-07 ***
## k 127.77529 26.81374 4.765 2.32e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4536 on 668 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 9.662e-06
## (7 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Error in numericDeriv(form[[3L]], names(ind), env, central = nDcentral) :
## Missing value or an infinity produced when evaluating the model
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 668 137.45
## 2 667 137.06 1 0.38606 1.8787 0.1709
## model AIC
## 1 3 6914.896
## 2 3a 6915.003
## 3 3b 6915.692
## 4 3c NA##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.88582 0.65606 1.350 0.177
## phi -0.01472 0.01648 -0.893 0.372
## alpha 0.88301 0.11088 7.964 7.21e-15 ***
## A 271.33123 53.95943 5.028 6.36e-07 ***
## k 127.77529 26.81374 4.765 2.32e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4536 on 668 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 9.662e-06
## (7 observations deleted due to missingness)summary
- add p model: fits
- add s model: fits
- add s+p model: does not fit
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 674 152.71
## 2 673 152.68 1 0.0292 0.1285 0.7201
## 3 666 136.87 7 15.8066 10.9877 3.553e-13 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3 6914.896
## 2 4 7029.273
## 3 5 7031.144
## 4 6 6916.058##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.88582 0.65606 1.350 0.177
## phi -0.01472 0.01648 -0.893 0.372
## alpha 0.88301 0.11088 7.964 7.21e-15 ***
## A 271.33123 53.95943 5.028 6.36e-07 ***
## k 127.77529 26.81374 4.765 2.32e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4536 on 668 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 9.662e-06
## (7 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.96139, p-value = 2.614e-12
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -8.552, p-value < 2.2e-16
## alternative hypothesis: two.sidedpredict and plot
plotting 2
M242 - Cascade Mixed Forest
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
## [1] "cannot plot observed vs. predicted"M261 - Sierran Steppe - Mixed Forest - Coniferous Forest - Alpine Meadow
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 326 100.337
## 2 325 100.079 1 0.258 0.8374 0.3608
## 3 158 52.814 167 47.265 0.8467 0.8555
## model AIC
## 1 1 3504.259
## 2 2 3505.412
## 3 3 1759.456##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -1.48606 1.41220 -1.052 0.2943
## phi 0.01272 0.04987 0.255 0.7990
## alpha 0.76925 0.26956 2.854 0.0049 **
## A 203.25021 140.15841 1.450 0.1490
## k 14.85544 10.51749 1.412 0.1598
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5782 on 158 degrees of freedom
##
## Number of iterations to convergence: 12
## Achieved convergence tolerance: 6.912e-06
## (167 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Error in numericDeriv(form[[3L]], names(ind), env, central = nDcentral) :
## Missing value or an infinity produced when evaluating the model
## Error in numericDeriv(form[[3L]], names(ind), env, central = nDcentral) :
## Missing value or an infinity produced when evaluating the model
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 158 52.814
## 2 157 52.358 1 0.45656 1.369 0.2438
## model AIC
## 1 3 1759.456
## 2 3a 1760.041
## 3 3b NA
## 4 3c NA##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -1.48606 1.41220 -1.052 0.2943
## phi 0.01272 0.04987 0.255 0.7990
## alpha 0.76925 0.26956 2.854 0.0049 **
## A 203.25021 140.15841 1.450 0.1490
## k 14.85544 10.51749 1.412 0.1598
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5782 on 158 degrees of freedom
##
## Number of iterations to convergence: 12
## Achieved convergence tolerance: 6.912e-06
## (167 observations deleted due to missingness)summary
- add p model: fits
- add s model: does not fit
- add s+p model: does not fit
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 324 96.856
## 2 323 96.193 1 0.664 2.2281 0.1365
## 3 156 50.242 167 45.951 0.8543 0.8414
## model AIC
## 1 3 1759.456
## 2 4 3496.641
## 3 5 3496.380
## 4 6 1755.317##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -1.51727 1.33141 -1.140 0.2562
## phi 0.02239 0.04716 0.475 0.6356
## alpha 0.65620 0.29602 2.217 0.0281 *
## a 0.00000 140.98559 0.000 1.0000
## b 195.96813 183.67096 1.067 0.2876
## c 113.88013 16.52715 6.890 1.29e-10 ***
## d 1.69907 0.94346 1.801 0.0737 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5675 on 156 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (167 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.98286, p-value = 0.04139
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = 0.2756, p-value = 0.7829
## alternative hypothesis: two.sidedpredict and plot
plotting 2
M262 - California coastal range - coniferous forest - open woodland - shrub meadow
Model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"- model can fit - but K is negative (only 19 observations) - model excluded
predict and plot
## [1] "cannot plot data with prediction"plotting 2
M313 - Arizona-New Mexico Mountains Semi-Desert - Open Woodland - Coniferous Forest - Alpine Meadow
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
M331 - Southern Rocky Mountain Steppe - Open Woodland - Coniferous Forest - Alpine Meadow
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
M332 - Middle Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
M333 - Northern Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
M334 - Black Hills Coniferous Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 299 124.348
## 2 298 124.343 1 0.005 0.0123 0.9116
## 3 212 86.586 86 37.757 1.0750 0.3349
## model AIC
## 1 1 3013.807
## 2 2 3015.794
## 3 3 2168.484##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.662886 1.134146 -0.584 0.55952
## phi 0.003057 0.035527 0.086 0.93151
## alpha 0.787867 0.134017 5.879 1.59e-08 ***
## A 119.692211 43.815875 2.732 0.00683 **
## k 51.043598 22.851590 2.234 0.02655 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6391 on 212 degrees of freedom
##
## Number of iterations to convergence: 7
## Achieved convergence tolerance: 1.69e-06
## (89 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (A * STDAGE_t2^s/(k^s + STDAGE_t2^s))
## Model 4: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2^s/(k^s + STDAGE_t2^s)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 212 86.586
## 2 211 86.584 1 0.00194 0.0047 0.9452
## 3 211 86.462 0 0.00000
## 4 210 86.173 1 0.28851 0.7031 0.4027
## model AIC
## 1 3 2168.484
## 2 3a 2170.479
## 3 3b 2170.172
## 4 3c 2171.446##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.662886 1.134146 -0.584 0.55952
## phi 0.003057 0.035527 0.086 0.93151
## alpha 0.787867 0.134017 5.879 1.59e-08 ***
## A 119.692211 43.815875 2.732 0.00683 **
## k 51.043598 22.851590 2.234 0.02655 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6391 on 212 degrees of freedom
##
## Number of iterations to convergence: 7
## Achieved convergence tolerance: 1.69e-06
## (89 observations deleted due to missingness)summary
- add p model: fits
- add s model: fits
- add s+p model: fits
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 297 124.07
## 2 296 124.07 1 0.000 0.0000 1.0000
## 3 210 86.54 86 37.528 1.0589 0.3661
## model AIC
## 1 3 2168.484
## 2 4 3017.126
## 3 5 3019.126
## 4 6 2172.369##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.662886 1.134146 -0.584 0.55952
## phi 0.003057 0.035527 0.086 0.93151
## alpha 0.787867 0.134017 5.879 1.59e-08 ***
## A 119.692211 43.815875 2.732 0.00683 **
## k 51.043598 22.851590 2.234 0.02655 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6391 on 212 degrees of freedom
##
## Number of iterations to convergence: 7
## Achieved convergence tolerance: 1.69e-06
## (89 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.92281, p-value = 3.121e-09
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -2.6099, p-value = 0.009057
## alternative hypothesis: two.sidedpredict and plot
plotting 2
M341 - Nevada-Utah Mountains Semi-Desert - Coniferous Forest - Alpine Meadow
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
Fitted parameters
Best / selected models by ecoprovince
| Code | Ecoregion | Sel.Mod.2 | Sel.Mod.3 | Best.Mod |
|---|---|---|---|---|
| 211 | Northeastern Mixed Forest | 3 | 6 | 6 |
| 212 | Laurentian Mixed Forest | 3c | 6 | 6 |
| 221 | Eastern Broadleaf Forest | 3b | 6 | 6 |
| 222 | Midwest Broadleaf Forest | 3 | 6 | 6 |
| 223 | Central Interior Broadleaf Forest | 3b | 6 | 6 |
| 231 | Southeastern Mixed Forest | 3c | 6 | 6 |
| 232 | Outer Coastal Plain Mixed Forest | 3c | 6 | 6 |
| 234 | Lower Mississippi Riverine Forest | 3 | 3 | 3 |
| 242 | Pacific Lowland Mixed Forest | NA | NA | NA |
| 251 | Prairie Parkland (Temperate) | 3b | 6 | 6 |
| 255 | Prairie Parkland (Subtropical) | 3a | 6 | 6 |
| 261 | California Coastal Chaparral Forest and Shrub | NA | NA | NA |
| 262 | California Dry Steppe | NA | NA | NA |
| 263 | California Coastal Steppe - Mixed Forest and Redwood Forest | NA | NA | NA |
| 313 | Colorado Plateau Semi-Desert | NA | NA | NA |
| 315 | Southwest Plateau and Plains Dry Steppe and Shrub | NA | NA | NA |
| 321 | Chihuahuan Semi-Desert | NA | NA | NA |
| 322 | American Semidesert and Desert | NA | NA | NA |
| 331 | Great Plains/Palouse Dry Steppe | NA | NA | NA |
| 332 | Great Plains Steppe | 3 | 6 | 6 |
| 341 | Intermountain Semi-Desert and Desert | NA | NA | NA |
| 342 | Intermountain Semi-Desert | NA | NA | NA |
| 411 | Everglades | NA | NA | NA |
| M211 | Adirondack-New England Mixed forest - Coniferous Forest - Alpine Meadow | 3b | 6 | 6 |
| M221 | Central Appalachian Broadleaf Forest - Coniferous Forest - Meadow | 3c | 3c | 3c |
| M223 | Ozark Broadleaf Forest Meadow | 3 | 3 | 3 |
| M231 | Ouachita Mixed Forest | 3 | 3 | 3 |
| M242 | Cascade Mixed Forest | NA | NA | NA |
| M261 | Sierran Steppe - Mixed Forest - Coniferous Forest - Alpine Meadow | 3 | 6 | 6 |
| M262 | California Coastal Range Coniferous Forest - Open Woodland - Shrub - Meadow | NA | NA | NA |
| M313 | Arizona-New Mexico Mountains Semi-Desert - Open Woodland - Coniferous Forest - Alpine Meadow | NA | NA | NA |
| M331 | Southern Rocky Mountain Steppe - Open Woodland - Coniferous Forest - Alpine Meadow | NA | NA | NA |
| M332 | Middle Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow | NA | NA | NA |
| M333 | Northern Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow | NA | NA | NA |
| M334 | Black Hills Coniferous Forest | 3 | 3 | 3 |
| M341 | Nevada-Utah Mountains Semi-Desert - Coniferous Forest - Alpine Meadow | NA | NA | NA |
table by ecoprovince
| Code | Ecoregion | region | n.obs | n.plots | ge | ge.variance | ge.2.5 | ge.97.5 | phi | phi.variance | phi.2.5 | phi.97.5 | alpha | alpha.variance | alpha.2.5 | alpha.97.5 | A | A.2.5 | A.97.5 | k | k.2.5 | k.97.5 | a | a.2.5 | a.97.5 | b | b.se | b.2.5 | b.97.5 | c | c.2.5 | c.97.5 | d | d.2.5 | d.97.5 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 211 | Northeastern Mixed Forest | east | 4838 | 2419 | 0.2877780 | 0.0287453 | -0.0446067 | 0.6201626 | 0.0213071 | 0.0000258 | 0.0113529 | 0.0312613 | 0.8506776 | 0.0010705 | 0.7865357 | 0.9148196 | 471.9581 | 403.50112 | 540.4152 | 191.34583 | 159.314916 | 223.37675 | 41.87458 | 37.982973 | 45.76619 | 114.43920 | NA | 104.05677 | 124.82163 | 111.99553 | 103.23997 | 120.7511 | 0.8929408 | 0.8078949 | 0.9779866 |
| 212 | Laurentian Mixed Forest | east | 12962 | 6481 | 0.2375598 | 0.0204719 | -0.0429069 | 0.5180266 | 0.0157806 | 0.0000164 | 0.0078382 | 0.0237231 | 0.7919628 | 0.0003927 | 0.7531169 | 0.8308086 | 123.9152 | 113.44105 | 134.3894 | 46.47178 | 43.311348 | 49.63222 | 24.94954 | 23.015693 | 26.88340 | 86.17965 | NA | 79.62083 | 92.73847 | 119.30997 | 108.73249 | 129.8875 | 1.2504323 | 1.1613832 | 1.3394814 |
| 221 | Eastern Broadleaf Forest | east | 5446 | 2723 | 0.2335590 | 0.0181260 | -0.0303756 | 0.4974937 | 0.0000000 | 0.0000161 | -0.0078628 | 0.0078628 | 0.8140497 | 0.0008966 | 0.7553476 | 0.8727517 | 317.0920 | 263.17442 | 371.0096 | 72.66406 | 54.460022 | 90.86810 | 29.92583 | 24.527782 | 35.32388 | 166.53295 | NA | 148.56212 | 184.50377 | 142.75973 | 118.81337 | 166.7061 | 1.3752196 | 1.2168728 | 1.5335664 |
| 222 | Midwest Broadleaf Forest | east | 3552 | 1776 | -0.3913884 | 0.0458539 | -0.8112717 | 0.0284948 | 0.0440710 | 0.0001297 | 0.0217421 | 0.0664000 | 0.8455980 | 0.0022501 | 0.7525864 | 0.9386096 | 510.0740 | 393.89458 | 626.2535 | 204.81027 | 152.111703 | 257.50884 | 28.12536 | 23.763183 | 32.48753 | 125.18955 | NA | 110.25587 | 140.12323 | 104.14395 | 92.34256 | 115.9453 | 1.0133386 | 0.8930635 | 1.1336136 |
| 223 | Central Interior Broadleaf Forest | east | 6388 | 3194 | -0.1998960 | 0.0133494 | -0.4264016 | 0.0266096 | 0.0000000 | 0.0000320 | -0.0110950 | 0.0110950 | 0.7613860 | 0.0010859 | 0.6967844 | 0.8259876 | 192.9556 | 171.30911 | 214.6021 | 40.23543 | 34.041793 | 46.42907 | 31.44045 | 25.722935 | 37.15796 | 117.40902 | NA | 107.20911 | 127.60894 | 106.43496 | 94.52851 | 118.3414 | 1.2637100 | 1.1181751 | 1.4092448 |
| 231 | Southeastern Mixed Forest | east | 7790 | 3895 | 1.9030316 | 0.0430033 | 1.4965246 | 2.3095385 | 0.0000000 | 0.0000219 | -0.0091714 | 0.0091714 | 0.7803165 | 0.0002322 | 0.7504464 | 0.8101865 | 131.0009 | 119.51983 | 142.4819 | 32.45598 | 30.141264 | 34.77070 | 25.28970 | 23.402041 | 27.17736 | 102.66171 | NA | 92.80545 | 112.51797 | 105.45703 | 90.17028 | 120.7438 | 1.4341063 | 1.3111268 | 1.5570858 |
| 232 | Outer Coastal Plain Mixed Forest | east | 7940 | 3970 | 1.1500067 | 0.0406599 | 0.7547318 | 1.5452815 | 0.0193128 | 0.0000277 | 0.0089922 | 0.0296334 | 0.8152161 | 0.0002219 | 0.7860133 | 0.8444188 | 143.4801 | 129.44490 | 157.5153 | 34.45142 | 31.602370 | 37.30047 | 29.73291 | 27.264532 | 32.20130 | 111.04165 | NA | 98.62444 | 123.45887 | 113.30665 | 93.44343 | 133.1699 | 1.4158887 | 1.2704611 | 1.5613163 |
| 234 | Lower Mississippi Riverine Forest | east | 830 | 415 | -0.0333131 | 0.1837739 | -0.8748068 | 0.8081806 | 0.0237660 | 0.0002904 | -0.0096837 | 0.0572157 | 0.7885292 | 0.0043191 | 0.6595244 | 0.9175340 | 773.1613 | 390.66059 | 1155.6620 | 245.90341 | 108.311676 | 383.49515 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 242 | Pacific Lowland Mixed Forest | pacific | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 251 | Prairie Parkland (Temperate) | east | 1392 | 696 | 0.5283403 | 0.1783177 | -0.3003368 | 1.3570175 | 0.0000000 | 0.0001229 | -0.0217547 | 0.0217547 | 0.7525580 | 0.0074718 | 0.5829283 | 0.9221876 | 131.1426 | 101.46422 | 160.8209 | 36.87788 | 30.265978 | 43.48978 | 20.68200 | 5.183318 | 36.18069 | 94.56775 | NA | 70.74096 | 118.39455 | 104.72342 | 83.37941 | 126.0674 | 1.1956744 | 0.8694895 | 1.5218593 |
| 255 | Prairie Parkland (Subtropical) | east | 444 | 222 | 0.1221031 | 0.3422036 | -1.0278180 | 1.2720243 | 0.0000000 | 0.0004029 | -0.0394581 | 0.0394581 | 0.7220666 | 0.0068888 | 0.5589130 | 0.8852202 | 350.5352 | -147.04769 | 848.1180 | 210.79807 | -192.422792 | 614.01894 | 24.95845 | 18.121437 | 31.79546 | 67.55150 | NA | 47.95070 | 87.15231 | 54.80781 | 45.02682 | 64.5888 | 0.8556175 | 0.6235703 | 1.0876647 |
| 261 | California Coastal Chaparral Forest and Shrub | pacific | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 262 | California Dry Steppe | pacific | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 263 | California Coastal Steppe - Mixed Forest and Redwood Forest | pacific | 4 | 2 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 313 | Colorado Plateau Semi-Desert | interior west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 315 | Southwest Plateau and Plains Dry Steppe and Shrub | interior west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 321 | Chihuahuan Semi-Desert | interior west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 322 | American Semidesert and Desert | interior west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 331 | Great Plains/Palouse Dry Steppe | interior west | 118 | 59 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 332 | Great Plains Steppe | interior west | 154 | 77 | 2.2294804 | 12.3806175 | -4.7306783 | 9.1896391 | 0.0046009 | 0.0015280 | -0.0727225 | 0.0819244 | 1.0341635 | 0.0773616 | 0.4839760 | 1.5843511 | 172.2171 | -48.75594 | 393.1901 | 97.50664 | -33.878566 | 228.89185 | 23.83275 | -5.242830 | 52.90833 | 51.23735 | NA | -18.14923 | 120.62392 | 116.03061 | -71.09191 | 303.1531 | 1.0694239 | -0.3789640 | 2.5178118 |
| 341 | Intermountain Semi-Desert and Desert | interior west | 4 | 2 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 342 | Intermountain Semi-Desert | interior west | 2 | 1 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 411 | Everglades | east | 66 | 33 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M211 | Adirondack-New England Mixed forest - Coniferous Forest - Alpine Meadow | east | 5108 | 2554 | 0.4171085 | 0.0227937 | 0.1211312 | 0.7130858 | 0.0247145 | 0.0000165 | 0.0167425 | 0.0326865 | 0.8146370 | 0.0006829 | 0.7634045 | 0.8658695 | 241.8804 | 209.67019 | 274.0905 | 69.02288 | 55.950986 | 82.09478 | 19.48247 | 13.935512 | 25.02943 | 147.87253 | NA | 129.20045 | 166.54461 | 174.87696 | 138.58584 | 211.1681 | 1.5230639 | 1.3260432 | 1.7200846 |
| M221 | Central Appalachian Broadleaf Forest - Coniferous Forest - Meadow | east | 5186 | 2593 | 1.2687929 | 0.0296116 | 0.9314425 | 1.6061433 | -0.0303623 | 0.0000197 | -0.0390669 | -0.0216577 | 0.8333259 | 0.0014275 | 0.7592578 | 0.9073941 | 150.8365 | 140.30543 | 161.3676 | 38.54357 | 36.536536 | 40.55061 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M223 | Ozark Broadleaf Forest Meadow | east | 602 | 301 | -0.6519872 | 0.0515526 | -1.0979110 | -0.2060634 | 0.0664387 | 0.0002983 | 0.0325206 | 0.1003568 | 0.8720875 | 0.0094986 | 0.6806772 | 1.0634977 | 328.2384 | 241.36099 | 415.1158 | 95.23106 | 59.188766 | 131.27336 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M231 | Ouachita Mixed Forest | east | 680 | 340 | 0.8858234 | 0.4304136 | -0.4023629 | 2.1740096 | -0.0147199 | 0.0002715 | -0.0470704 | 0.0176306 | 0.8830080 | 0.0122945 | 0.6652915 | 1.1007244 | 271.3312 | 165.38073 | 377.2817 | 127.77529 | 75.125933 | 180.42465 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M242 | Cascade Mixed Forest | pacific | 34 | 17 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M261 | Sierran Steppe - Mixed Forest - Coniferous Forest - Alpine Meadow | pacific | 330 | 165 | -1.5172712 | 1.7726606 | -4.1471947 | 1.1126523 | 0.0223906 | 0.0022241 | -0.0707641 | 0.1155453 | 0.6562001 | 0.0876307 | 0.0714661 | 1.2409341 | 203.2502 | -73.57555 | 480.0760 | 14.85544 | -5.917571 | 35.62846 | 0.00000 | -278.487071 | 278.48707 | 195.96813 | NA | -166.83483 | 558.77109 | 113.88013 | 81.23426 | 146.5260 | 1.6990664 | -0.1645364 | 3.5626693 |
| M262 | California Coastal Range Coniferous Forest - Open Woodland - Shrub - Meadow | interior west | 8 | 4 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M313 | Arizona-New Mexico Mountains Semi-Desert - Open Woodland - Coniferous Forest - Alpine Meadow | interior west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M331 | Southern Rocky Mountain Steppe - Open Woodland - Coniferous Forest - Alpine Meadow | interior west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M332 | Middle Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow | interior west | 20 | 10 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M333 | Northern Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow | interior west | 22 | 11 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M334 | Black Hills Coniferous Forest | interior west | 306 | 153 | -0.6628862 | 1.2862864 | -2.8985335 | 1.5727610 | 0.0030572 | 0.0012622 | -0.0669749 | 0.0730893 | 0.7878674 | 0.0179606 | 0.5236907 | 1.0520442 | 119.6922 | 33.32161 | 206.0628 | 51.04360 | 5.998156 | 96.08904 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M341 | Nevada-Utah Mountains Semi-Desert - Coniferous Forest - Alpine Meadow | interior west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
plot ge
map
## OGR data source with driver: ESRI Shapefile
## Source: "C:\Users\hogan.jaaron\Dropbox\FIA_R\Mapping\S_USA.EcoMapProvinces\S_USA.EcoMapProvinces.shp", layer: "S_USA.EcoMapProvinces"
## with 37 features
## It has 17 fields
## Integer64 fields read as strings: PROVINCE_ PROVINCE_I
plot phi (effect of DeltaPDSI)
plot alpha (biomass compensation effect)
plot A (asymptote of B)
## Warning: Removed 19 rows containing missing values (geom_point).
plot k (stand age at half biomass asymptote)
## Warning: Removed 19 rows containing missing values (geom_point).
Caclulations - weighted averages
ge (stand biomass enhancement factor in % 2000-2021)
## region weighted.ge weighted.ge.std_Error 95 % CI, upper
## 1 entire US 0.566036010 0.057633715 0.678998091
## 2 pacific -0.007795900 0.006840941 0.005612345
## 3 east 0.571644372 0.056342414 0.682075503
## 4 interior west 0.002187538 0.010018934 0.021824648
## 95 % CI, lower
## 1 0.45307393
## 2 -0.02120415
## 3 0.46121324
## 4 -0.01744957phi (effect of DeltaPDSI)
## region weighted.phi weighted.phi.std_Error 95 % CI, upper
## 1 entire US 1.004334e-02 0.0017032896 0.0133817874
## 2 pacific 1.150454e-04 0.0002423134 0.0005899797
## 3 east 9.902697e-03 0.0016748263 0.0131853562
## 4 interior west 2.559775e-05 0.0001934853 0.0004048289
## 95 % CI, lower
## 1 0.0067048921
## 2 -0.0003598890
## 3 0.0066200371
## 4 -0.0003536334alpha (biomass compensation effect)
## region weighted.alpha weighted.alpha.std_Error 95 % CI, upper
## 1 entire US 0.801557954 0.0087472586 0.818702581
## 2 pacific 0.003371626 0.0015210066 0.006352799
## 3 east 0.791952893 0.0085643792 0.808739076
## 4 interior west 0.006233435 0.0009232988 0.008043101
## 95 % CI, lower
## 1 0.7844133275
## 2 0.0003904528
## 3 0.7751667100
## 4 0.0044237698A (asymptote of forest biomass in Mg/ha)
## region weighted.A
## 1 entire US 223.1264
## 2 pacific 182.2624
## 3 east 224.6030
## 4 interior west 0.0000K (stand age at half maturation in years)
## region weighted.k
## 1 entire US 70.31344
## 2 pacific 13.32146
## 3 east 70.86571
## 4 interior west 48.32076Model Bookeeping
1. Delta-B due to Delta-STDAGE
2. Delta-B due to Delta-Year (ge)
make a fig
## Warning: Removed 12504 rows containing missing values (geom_point).
3. stand age densities
make a fig
## Warning: package 'ggridges' was built under R version 4.2.2## Picking joint bandwidth of 7.36
Analysis 2: Temporally-balanced, No-harvest
211 - Northeastern Mixed Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 3758 873.45
## 2 3757 871.73 1 1.722 7.4221 0.006473 **
## 3 3725 801.01 32 70.721 10.2776 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 40904.91
## 2 2 40899.49
## 3 3 40329.41##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.44857 0.20583 2.179 0.02937 *
## phi 0.01735 0.00574 3.023 0.00252 **
## alpha 1.18650 0.06958 17.052 < 2e-16 ***
## A 449.33176 38.06338 11.805 < 2e-16 ***
## k 191.61411 18.22818 10.512 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4637 on 3725 degrees of freedom
##
## Number of iterations to convergence: 7
## Achieved convergence tolerance: 1.391e-06
## (32 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Error in numericDeriv(form[[3L]], names(ind), env, central = nDcentral) :
## Missing value or an infinity produced when evaluating the model
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 3725 801.01
## 2 3724 801.01 1 0.00012996 6e-04 0.9804
## model AIC
## 1 3 40329.41
## 2 3a 40331.41
## 3 3b 40326.08
## 4 3c NA##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (A * STDAGE_t2^s/(k^s +
## STDAGE_t2^s))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 4.297e-01 2.039e-01 2.107 0.03515 *
## phi 1.696e-02 5.747e-03 2.951 0.00319 **
## alpha 1.191e+00 7.011e-02 16.994 < 2e-16 ***
## A 3.140e+02 4.544e+01 6.910 5.69e-12 ***
## k 1.031e+02 2.332e+01 4.422 1.01e-05 ***
## s 1.165e+00 7.803e-02 14.924 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4634 on 3724 degrees of freedom
##
## Number of iterations to convergence: 8
## Achieved convergence tolerance: 4.238e-06
## (32 observations deleted due to missingness)summary
- add p model: fits
- add s model: fits
- add s+p model: does not fit
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 3756 857.29
## 2 3755 855.77 1 1.514 6.6444 0.009985 **
## 3 3723 781.01 32 74.766 11.1376 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3b 40326.08
## 2 4 40838.67
## 3 5 40834.02
## 4 6 40239.10##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 6.302e-01 2.188e-01 2.880 0.00400 **
## phi 1.693e-02 5.673e-03 2.985 0.00286 **
## alpha 1.170e+00 6.853e-02 17.070 < 2e-16 ***
## a 3.894e+01 2.230e+00 17.459 < 2e-16 ***
## b 1.122e+02 6.313e+00 17.780 < 2e-16 ***
## c 1.162e+02 5.721e+00 20.307 < 2e-16 ***
## d 9.315e-01 5.285e-02 17.626 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.458 on 3723 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (32 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.98702, p-value < 2.2e-16
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -25.889, p-value < 2.2e-16
## alternative hypothesis: two.sidedpredict and plot
plotting 2
212 - Laurentian Mixed Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 10460 3892.5
## 2 10457 3882.9 3 9.59 8.6080 1.054e-05 ***
## 3 7874 2744.9 2583 1137.99 1.2638 4.800e-14 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 109465.57
## 2 2 109421.55
## 3 3 82461.78##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 6.899e-02 1.466e-01 0.471 0.638
## phi 2.316e-02 4.553e-03 5.088 3.71e-07 ***
## alpha 9.137e-01 4.640e-02 19.693 < 2e-16 ***
## A 1.839e+02 8.007e+00 22.968 < 2e-16 ***
## k 6.688e+01 3.214e+00 20.812 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5904 on 7874 degrees of freedom
##
## Number of iterations to convergence: 5
## Achieved convergence tolerance: 5.225e-06
## (2591 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (A * STDAGE_t2^s/(k^s + STDAGE_t2^s))
## Model 4: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2^s/(k^s + STDAGE_t2^s)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 7874 2744.9
## 2 7873 2740.5 1 4.459 12.809 0.000347 ***
## 3 7873 2744.9 0 0.000
## 4 7872 2710.2 1 34.680 100.731 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3 82461.78
## 2 3a 82450.98
## 3 3b 82463.74
## 4 3c 82365.56##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) *
## A * STDAGE_t2^s/(k^s + STDAGE_t2^s)))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.511e-01 1.515e-01 0.997 0.319
## phi 2.196e-02 4.511e-03 4.869 1.14e-06 ***
## alpha 9.058e-01 4.340e-02 20.871 < 2e-16 ***
## A 1.249e+02 6.258e+00 19.957 < 2e-16 ***
## k 4.582e+01 1.993e+00 22.988 < 2e-16 ***
## p 1.788e-01 1.531e-02 11.680 < 2e-16 ***
## s 2.094e+00 1.541e-01 13.585 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5868 on 7872 degrees of freedom
##
## Number of iterations to convergence: 11
## Achieved convergence tolerance: 7.906e-06
## (2591 observations deleted due to missingness)summary
- add p model: fits
- add s model: fits
- add s+p model: fits
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 10458 3839.4
## 2 10455 3831.6 3 7.76 7.0593 9.764e-05 ***
## 3 7872 2703.3 2583 1128.38 1.2721 9.390e-15 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3c 82365.56
## 2 4 109325.84
## 3 5 109286.47
## 4 6 82345.24##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.809e-01 1.532e-01 1.180 0.238
## phi 2.119e-02 4.501e-03 4.709 2.53e-06 ***
## alpha 9.083e-01 4.320e-02 21.026 < 2e-16 ***
## a 2.358e+01 1.308e+00 18.029 < 2e-16 ***
## b 8.645e+01 3.883e+00 22.261 < 2e-16 ***
## c 1.254e+02 7.218e+00 17.369 < 2e-16 ***
## d 1.351e+00 6.256e-02 21.593 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.586 on 7872 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (2591 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
predict and plot
plotting 2
221 - Eastern Broadleaf Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 4456 722.50
## 2 4455 722.49 1 0.002 0.0154 0.9013
## 3 4421 670.60 34 51.899 10.0633 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 48766.23
## 2 2 48768.22
## 3 3 48166.70##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 5.303e-01 1.674e-01 3.169 0.00154 **
## phi -9.616e-04 4.453e-03 -0.216 0.82905
## alpha 9.230e-01 5.191e-02 17.782 < 2e-16 ***
## A 4.435e+02 2.951e+01 15.031 < 2e-16 ***
## k 1.434e+02 1.095e+01 13.096 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3895 on 4421 degrees of freedom
##
## Number of iterations to convergence: 5
## Achieved convergence tolerance: 6.44e-06
## (34 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Error in numericDeriv(form[[3L]], names(ind), env, central = nDcentral) :
## Missing value or an infinity produced when evaluating the model
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 4421 670.60
## 2 4420 669.49 1 1.1033 7.2841 0.006983 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3 48166.70
## 2 3a 48161.41
## 3 3b 48144.77
## 4 3c NA##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (A * STDAGE_t2^s/(k^s +
## STDAGE_t2^s))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.593464 0.171933 3.452 0.000562 ***
## phi -0.001691 0.004437 -0.381 0.703039
## alpha 0.932788 0.052390 17.805 < 2e-16 ***
## A 269.299929 21.851620 12.324 < 2e-16 ***
## k 61.793839 6.743968 9.163 < 2e-16 ***
## s 1.336106 0.072380 18.459 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3885 on 4420 degrees of freedom
##
## Number of iterations to convergence: 7
## Achieved convergence tolerance: 8.634e-06
## (34 observations deleted due to missingness)summary
- add p model: fits
- add s model: fits
- add s+p model: does not fit
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 4454 713.75
## 2 4453 713.75 1 0.000 0.000 1
## 3 4419 662.39 34 51.355 10.076 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3b 48144.77
## 2 4 48715.91
## 3 5 48717.91
## 4 6 48116.23##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 6.043e-01 1.720e-01 3.512 0.000449 ***
## phi 0.000e+00 4.436e-03 0.000 1.000000
## alpha 9.248e-01 5.169e-02 17.891 < 2e-16 ***
## a 2.791e+01 3.095e+00 9.018 < 2e-16 ***
## b 1.518e+02 8.724e+00 17.399 < 2e-16 ***
## c 1.330e+02 1.063e+01 12.513 < 2e-16 ***
## d 1.318e+00 8.223e-02 16.029 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3872 on 4419 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (34 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.98522, p-value < 2.2e-16
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -27.874, p-value < 2.2e-16
## alternative hypothesis: two.sidedpredict and plot
plotting 2
222 - Midwest Broadleaf Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 2793 944.73
## 2 2792 941.04 1 3.698 10.9728 0.0009364 ***
## 3 2140 667.70 652 273.335 1.3436 7.999e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## model AIC
## 1 1 30090.45
## 2 2 30081.49
## 3 3 23131.25##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.43802 0.24074 -1.820 0.06897 .
## phi 0.04284 0.01303 3.287 0.00103 **
## alpha 0.94629 0.07841 12.069 < 2e-16 ***
## A 555.26223 80.49540 6.898 6.92e-12 ***
## k 234.54724 37.91141 6.187 7.34e-10 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5586 on 2140 degrees of freedom
##
## Number of iterations to convergence: 7
## Achieved convergence tolerance: 3.669e-06
## (653 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Error in numericDeriv(form[[3L]], names(ind), env, central = nDcentral) :
## Missing value or an infinity produced when evaluating the model
## Error in numericDeriv(form[[3L]], names(ind), env, central = nDcentral) :
## Missing value or an infinity produced when evaluating the model
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 2140 667.70
## 2 2139 665.23 1 2.4744 7.9562 0.004837 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3 23131.25
## 2 3a 23125.29
## 3 3b NA
## 4 3c NA##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) *
## A * STDAGE_t2/(k + STDAGE_t2)))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.42210 0.24225 -1.742 0.081579 .
## phi 0.04353 0.01303 3.341 0.000848 ***
## alpha 0.96338 0.07847 12.277 < 2e-16 ***
## A 415.29178 63.16060 6.575 6.09e-11 ***
## k 145.60494 32.08423 4.538 5.99e-06 ***
## p -0.02285 0.01221 -1.871 0.061451 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5577 on 2139 degrees of freedom
##
## Number of iterations to convergence: 9
## Achieved convergence tolerance: 5.52e-06
## (653 observations deleted due to missingness)summary
- add p model: fits
- add s model: does not fit
- add s+p model: does not fit
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 2791 928.22
## 2 2790 924.40 1 3.826 11.5480 0.0006877 ***
## 3 2138 650.78 652 273.614 1.3787 8.666e-08 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3a 23125.29
## 2 4 30045.16
## 3 5 30035.61
## 4 6 23080.20##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.30194 0.25505 -1.184 0.236605
## phi 0.04571 0.01297 3.523 0.000436 ***
## alpha 0.97764 0.07473 13.083 < 2e-16 ***
## a 25.34285 2.55168 9.932 < 2e-16 ***
## b 125.49277 8.96784 13.994 < 2e-16 ***
## c 105.73419 7.14126 14.806 < 2e-16 ***
## d 1.03559 0.07112 14.561 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5517 on 2138 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (653 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.96192, p-value < 2.2e-16
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -15.636, p-value < 2.2e-16
## alternative hypothesis: two.sidedpredict and plot
plotting 2
223 - Central Interior Broadleaf Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 5108 929.31
## 2 5107 926.24 1 3.07 16.9250 3.95e-05 ***
## 3 4257 767.63 850 158.62 1.0349 0.2549
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 53477.85
## 2 2 53462.94
## 3 3 44740.59##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.037514 0.143266 0.262 0.79345
## phi -0.017291 0.006144 -2.814 0.00491 **
## alpha 0.849970 0.056531 15.036 < 2e-16 ***
## A 290.320466 15.959640 18.191 < 2e-16 ***
## k 87.121972 6.114438 14.249 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4246 on 4257 degrees of freedom
##
## Number of iterations to convergence: 7
## Achieved convergence tolerance: 1.703e-06
## (850 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Error in numericDeriv(form[[3L]], names(ind), env, central = nDcentral) :
## Missing value or an infinity produced when evaluating the model
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 4257 767.63
## 2 4256 767.38 1 0.24491 1.3583 0.2439
## model AIC
## 1 3 44740.59
## 2 3a 44741.23
## 3 3b 44708.00
## 4 3c NA##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (A * STDAGE_t2^s/(k^s +
## STDAGE_t2^s))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.072750 0.145011 0.502 0.61591
## phi -0.017575 0.006106 -2.878 0.00402 **
## alpha 0.862833 0.056925 15.157 < 2e-16 ***
## A 187.602452 11.090419 16.916 < 2e-16 ***
## k 40.382048 3.004623 13.440 < 2e-16 ***
## s 1.484595 0.085160 17.433 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.423 on 4256 degrees of freedom
##
## Number of iterations to convergence: 9
## Achieved convergence tolerance: 1.543e-06
## (850 observations deleted due to missingness)summary
- add p model: fits
- add s model: fits
- add s+p model: does not fit
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 5106 913.48
## 2 5105 913.48 1 0.00 0.0000 0.99999
## 3 4255 751.00 850 162.49 1.0831 0.06339 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3b 44708.00
## 2 4 53394.02
## 3 5 53396.02
## 4 6 44651.23##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.088713 0.134486 -0.66 0.51
## phi 0.000000 0.006259 0.00 1.00
## alpha 0.851800 0.055876 15.24 <2e-16 ***
## a 29.949354 2.877660 10.41 <2e-16 ***
## b 116.927942 5.395173 21.67 <2e-16 ***
## c 104.057685 5.723300 18.18 <2e-16 ***
## d 1.209447 0.071748 16.86 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4201 on 4255 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (850 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
predict and plot
plotting 2
231 - Southeastern Mixed Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 6088 1450.4
## 2 6087 1450.3 1 0.128 0.5378 0.4634
## 3 5968 1320.5 119 129.735 4.9270 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 66409.03
## 2 2 66410.49
## 3 3 64983.46##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.525776 0.182829 8.345 <2e-16 ***
## phi -0.002669 0.004681 -0.570 0.569
## alpha 0.825622 0.047959 17.215 <2e-16 ***
## A 248.135533 10.671797 23.252 <2e-16 ***
## k 65.157321 2.827731 23.042 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4704 on 5968 degrees of freedom
##
## Number of iterations to convergence: 5
## Achieved convergence tolerance: 7.173e-06
## (119 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (A * STDAGE_t2^s/(k^s + STDAGE_t2^s))
## Model 4: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2^s/(k^s + STDAGE_t2^s)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 5968 1320.5
## 2 5967 1319.8 1 0.7707 3.4845 0.062 .
## 3 5967 1320.1 0 0.0000
## 4 5966 1308.2 1 11.9907 54.6854 1.609e-13 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3 64983.46
## 2 3a 64981.97
## 3 3b 64983.61
## 4 3c 64931.11##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) *
## A * STDAGE_t2^s/(k^s + STDAGE_t2^s)))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.620931 0.188921 8.580 < 2e-16 ***
## phi -0.002900 0.004649 -0.624 0.533
## alpha 0.835793 0.046899 17.821 < 2e-16 ***
## A 159.443801 8.574543 18.595 < 2e-16 ***
## k 34.733065 1.937860 17.923 < 2e-16 ***
## p 0.098487 0.014242 6.915 5.16e-12 ***
## s 1.692332 0.115606 14.639 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4683 on 5966 degrees of freedom
##
## Number of iterations to convergence: 13
## Achieved convergence tolerance: 4.557e-06
## (119 observations deleted due to missingness)summary
- add p model: fits
- add s model: fits
- add s+p model: fits
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 6086 1437.5
## 2 6085 1437.5 1 0.00 0.0000 1
## 3 5966 1307.1 119 130.34 4.9994 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3c 64931.11
## 2 4 66358.45
## 3 5 66360.45
## 4 6 64926.45##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.568e+00 1.857e-01 8.447 <2e-16 ***
## phi 0.000e+00 4.644e-03 0.000 1
## alpha 8.342e-01 4.686e-02 17.801 <2e-16 ***
## a 1.689e+01 1.638e+00 10.310 <2e-16 ***
## b 1.280e+02 7.659e+00 16.707 <2e-16 ***
## c 1.380e+02 1.647e+01 8.376 <2e-16 ***
## d 1.788e+00 1.035e-01 17.274 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4681 on 5966 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (119 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
predict and plot
plotting 2
232 - Outer Coastal Plain Mixed Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 6290 2432.4
## 2 6289 2429.8 1 2.678 6.9325 0.008485 **
## 3 6149 2238.4 140 191.372 3.7551 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 70632.57
## 2 2 70627.64
## 3 3 69028.99##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 9.499e-01 1.980e-01 4.796 1.65e-06 ***
## phi 9.452e-03 5.430e-03 1.741 0.0818 .
## alpha 7.839e-01 4.707e-02 16.653 < 2e-16 ***
## A 2.624e+02 1.416e+01 18.536 < 2e-16 ***
## k 6.860e+01 3.799e+00 18.056 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6033 on 6149 degrees of freedom
##
## Number of iterations to convergence: 5
## Achieved convergence tolerance: 6.143e-06
## (142 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (A * STDAGE_t2^s/(k^s + STDAGE_t2^s))
## Model 4: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2^s/(k^s + STDAGE_t2^s)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 6149 2238.4
## 2 6148 2232.1 1 6.2484 17.21 3.392e-05 ***
## 3 6148 2238.2 0 0.0000
## 4 6147 2211.9 1 26.3325 73.18 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3 69028.99
## 2 3a 69013.78
## 3 3b 69030.55
## 4 3c 68959.72##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) *
## A * STDAGE_t2^s/(k^s + STDAGE_t2^s)))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.057e+00 2.048e-01 5.161 2.54e-07 ***
## phi 1.114e-02 5.375e-03 2.072 0.0383 *
## alpha 8.077e-01 4.419e-02 18.279 < 2e-16 ***
## A 1.616e+02 9.596e+00 16.837 < 2e-16 ***
## k 3.606e+01 2.087e+00 17.281 < 2e-16 ***
## p 1.288e-01 1.577e-02 8.164 3.90e-16 ***
## s 1.880e+00 1.460e-01 12.879 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5999 on 6147 degrees of freedom
##
## Number of iterations to convergence: 17
## Achieved convergence tolerance: 8.126e-06
## (142 observations deleted due to missingness)summary
- add p model: fits
- add s model: fits
- add s+p model: fits
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 6288 2414.5
## 2 6287 2411.3 1 3.197 8.3359 0.0039 **
## 3 6147 2210.9 140 200.339 3.9785 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3c 68959.72
## 2 4 70589.95
## 3 5 70583.61
## 4 6 68957.08##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.040e+00 2.036e-01 5.106 3.39e-07 ***
## phi 1.097e-02 5.372e-03 2.042 0.0412 *
## alpha 8.063e-01 4.417e-02 18.253 < 2e-16 ***
## a 2.148e+01 1.831e+00 11.732 < 2e-16 ***
## b 1.294e+02 8.811e+00 14.682 < 2e-16 ***
## c 1.367e+02 1.749e+01 7.818 6.26e-15 ***
## d 1.672e+00 1.093e-01 15.298 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5997 on 6147 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (142 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
predict and plot
plotting 2
234 - Lower Mississippi Riverine Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 675 158.75
## 2 674 157.88 1 0.8713 3.7194 0.0542 .
## 3 652 137.37 22 20.5192 4.4270 1.476e-10 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 7483.277
## 2 2 7481.546
## 3 3 7228.523##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.05481 0.48055 0.114 0.909231
## phi 0.02653 0.01807 1.468 0.142506
## alpha 0.89149 0.10373 8.594 < 2e-16 ***
## A 622.17392 149.14819 4.172 3.44e-05 ***
## k 187.66098 51.26819 3.660 0.000272 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.459 on 652 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 3.757e-06
## (27 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Error in nls(get(paste("f_", Mod.Sel1, "c", sep = "")), data = G_234, :
## number of iterations exceeded maximum of 50
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 652 137.37
## 2 651 137.32 1 0.049153 0.233 0.6294
## model AIC
## 1 3 7228.523
## 2 3a 7230.288
## 3 3b 7230.439
## 4 3c NA##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.05481 0.48055 0.114 0.909231
## phi 0.02653 0.01807 1.468 0.142506
## alpha 0.89149 0.10373 8.594 < 2e-16 ***
## A 622.17392 149.14819 4.172 3.44e-05 ***
## k 187.66098 51.26819 3.660 0.000272 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.459 on 652 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 3.757e-06
## (27 observations deleted due to missingness)summary
- add p model: fits
- add s model: fits
- add s+p model: does not fit
model selection 3
## Error in nls(f_6, data = G_234, start = c(ge = ge.start, phi = phi.start, :
## Convergence failure: iteration limit reached without convergence (10)
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 673 158.11
## 2 672 157.27 1 0.8398 3.5885 0.05861 .
## 3 794 176.36 -122 -19.0827 0.6683 0.99681
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3 7228.523
## 2 4 7484.532
## 3 5 7482.921
## 4 6 8723.879##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.05481 0.48055 0.114 0.909231
## phi 0.02653 0.01807 1.468 0.142506
## alpha 0.89149 0.10373 8.594 < 2e-16 ***
## A 622.17392 149.14819 4.172 3.44e-05 ***
## k 187.66098 51.26819 3.660 0.000272 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.459 on 652 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 3.757e-06
## (27 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.96038, p-value = 2.573e-12
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -9.4259, p-value < 2.2e-16
## alternative hypothesis: two.sidedpredict and plot
plotting 2
242 - Pacific Lowland Mixed Forest
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
## [1] "cannot plot observed vs. predicted"251 - Prairie Parkland (Temperate)
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 1213 319.61
## 2 1212 319.58 1 0.028 0.1069 0.7438
## 3 865 177.86 347 141.724 1.9864 8.171e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 12758.145
## 2 2 12760.038
## 3 3 9002.571##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.79489 0.50209 1.583 0.114
## phi -0.01295 0.01145 -1.131 0.258
## alpha 0.76389 0.11156 6.847 1.43e-11 ***
## A 235.64874 34.70425 6.790 2.08e-11 ***
## k 100.50604 16.52225 6.083 1.77e-09 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4534 on 865 degrees of freedom
##
## Number of iterations to convergence: 5
## Achieved convergence tolerance: 7.737e-06
## (348 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Error in numericDeriv(form[[3L]], names(ind), env, central = nDcentral) :
## Missing value or an infinity produced when evaluating the model
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 865 177.86
## 2 864 177.47 1 0.38965 1.897 0.1688
## model AIC
## 1 3 9002.571
## 2 3a 9002.663
## 3 3b 8999.426
## 4 3c NA##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (A * STDAGE_t2^s/(k^s +
## STDAGE_t2^s))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.75249 0.49320 1.526 0.127
## phi -0.01115 0.01148 -0.971 0.332
## alpha 0.77831 0.11201 6.949 7.26e-12 ***
## A 151.42691 24.69003 6.133 1.31e-09 ***
## k 45.36071 9.02675 5.025 6.11e-07 ***
## s 1.46235 0.21493 6.804 1.90e-11 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4524 on 864 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 4.888e-06
## (348 observations deleted due to missingness)summary
- add p model: fits
- add s model: fits
- add s+p model: does not fit
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 1211 309.99
## 2 1210 309.99 1 0 0.0000 0.9999
## 3 863 175.99 347 134 1.8935 7.262e-14 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3b 8999.426
## 2 4 12724.990
## 3 5 12726.990
## 4 6 8997.414##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.59354 0.46513 1.276 0.202271
## phi 0.00000 0.01172 0.000 1.000000
## alpha 0.76837 0.11289 6.806 1.87e-11 ***
## a 24.43593 7.17778 3.404 0.000694 ***
## b 91.93815 13.22793 6.950 7.19e-12 ***
## c 114.37086 17.39595 6.575 8.44e-11 ***
## d 1.22793 0.19996 6.141 1.25e-09 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4516 on 863 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (348 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.97047, p-value = 2.825e-12
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -8.0023, p-value = 1.222e-15
## alternative hypothesis: two.sidedpredict and plot
plotting 2
255 - Prairie Parkland (Subtropical)
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 408 218.09
## 2 407 217.93 1 0.163 0.3045 0.5814
## 3 383 184.09 24 33.834 2.9330 7.466e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 4302.110
## 2 2 4303.803
## 3 3 4088.337##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.32186 0.52276 -0.616 0.538
## phi -0.02611 0.02207 -1.183 0.238
## alpha 0.63678 0.16053 3.967 8.70e-05 ***
## A 190.83546 37.83297 5.044 7.05e-07 ***
## k 52.67803 12.46716 4.225 2.99e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6933 on 383 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 2.266e-06
## (24 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Error in numericDeriv(form[[3L]], names(ind), env, central = nDcentral) :
## Missing value or an infinity produced when evaluating the model
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 383 184.09
## 2 382 180.46 1 3.637 7.6991 0.005796 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3 4088.337
## 2 3a 4082.594
## 3 3b 4088.036
## 4 3c NA##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) *
## A * STDAGE_t2/(k + STDAGE_t2)))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.23186 0.54320 -0.427 0.66973
## phi -0.02621 0.02170 -1.207 0.22799
## alpha 0.62154 0.14827 4.192 3.44e-05 ***
## A 285.12305 130.98147 2.177 0.03011 *
## k 127.22908 88.65035 1.435 0.15205
## p 0.04230 0.01344 3.147 0.00178 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6873 on 382 degrees of freedom
##
## Number of iterations to convergence: 17
## Achieved convergence tolerance: 8.235e-06
## (24 observations deleted due to missingness)summary
- add p model: fits
- add s model: fits
- add s+p model: does not fit
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 406 207.53
## 2 405 207.47 1 0.063 0.1225 0.7265
## 3 381 171.16 24 36.312 3.3680 3.26e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3a 4082.594
## 2 4 4285.720
## 3 5 4287.596
## 4 6 4064.072##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.3922 0.4814 -0.815 0.416
## phi 0.0000 0.0214 0.000 1.000
## alpha 0.6720 0.1449 4.637 4.87e-06 ***
## a 24.3767 3.5861 6.798 4.12e-11 ***
## b 78.2867 10.9062 7.178 3.72e-12 ***
## c 56.0639 6.1664 9.092 < 2e-16 ***
## d 0.9506 0.1372 6.928 1.83e-11 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6702 on 381 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (24 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.93922, p-value = 1.682e-11
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -3.7338, p-value = 0.0001886
## alternative hypothesis: two.sidedpredict and plot
plotting 2
261 - California Coastal Chaparral Forest and Shrub
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
add p model: does not fit
add s model: does not fit
add s+p model: does not fit
unable to fit model (only 64 observations)
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
## [1] "cannot plot observed vs. predicted"262 - California Dry Steppe
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
add p model: does not fit
add s model: does not fit
add s+p model: does not fit
unable to fit model (0 observations)
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
## [1] "cannot plot observed vs. predicted"263 - California Coastal Steppe - Mixed Forest and Redwood Forest
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
## [1] "cannot plot observed vs. predicted"313 - Colorado Plateau Semi-Desert
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
## [1] "cannot plot observed vs. predicted"315 - Southwest Plateau and Plains Dry Steppe and Shrub
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
## [1] "cannot plot observed vs. predicted"321 - Chihuahuan Semi-Desert
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
## [1] "cannot plot observed vs. predicted"322 - American Semidesert and Desert
model selection 1
## Error in if (any(nEQ <- vNms != make.names(vNms))) vNms[nEQ] <- paste0("`", :
## missing value where TRUE/FALSE needed## Error in if (any(nEQ <- vNms != make.names(vNms))) vNms[nEQ] <- paste0("`", :
## missing value where TRUE/FALSE needed## Error in if (any(nEQ <- vNms != make.names(vNms))) vNms[nEQ] <- paste0("`", :
## missing value where TRUE/FALSE needed## model AIC
## 1 1 NA
## 2 2 NA
## 3 3 NA## Warning in min(AIC1_322$AIC, na.rm = T): no non-missing arguments to min;
## returning Inf## Error in h(simpleError(msg, call)) :
## error in evaluating the argument 'object' in selecting a method for function 'summary': object 'nls_322.' not foundsummary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
## [1] "cannot plot observed vs. predicted"- Cannot fit model
- not enough data (only 3 observations)
331 - Great Plains/Palouse Dry Steppe
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
## [1] "cannot plot observed vs. predicted"- Cannot fit model
332 - Great Plains Steppe
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 141 88.067
## 2 140 88.063 1 0.0038 0.0060 0.9386
## 3 126 75.542 14 12.5205 1.4917 0.1233
## model AIC
## 1 1 1555.082
## 2 2 1557.076
## 3 3 1424.171##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.44400 2.00329 0.222 0.8250
## phi 0.02229 0.04268 0.522 0.6024
## alpha 1.04434 0.23175 4.506 1.49e-05 ***
## A 182.12937 106.18951 1.715 0.0888 .
## k 85.27547 57.45271 1.484 0.1402
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7743 on 126 degrees of freedom
##
## Number of iterations to convergence: 5
## Achieved convergence tolerance: 5.842e-06
## (15 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Error in nls(get(paste("f_", Mod.Sel1, "a", sep = "")), data = G_332, :
## number of iterations exceeded maximum of 50
## Error in nls(get(paste("f_", Mod.Sel1, "b", sep = "")), data = G_332, :
## number of iterations exceeded maximum of 50
## Error in numericDeriv(form[[3L]], names(ind), env, central = nDcentral) :
## Missing value or an infinity produced when evaluating the model
## model AIC
## 1 3 1424.171
## 2 3a NA
## 3 3b NA
## 4 3c NA##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.44400 2.00329 0.222 0.8250
## phi 0.02229 0.04268 0.522 0.6024
## alpha 1.04434 0.23175 4.506 1.49e-05 ***
## A 182.12937 106.18951 1.715 0.0888 .
## k 85.27547 57.45271 1.484 0.1402
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7743 on 126 degrees of freedom
##
## Number of iterations to convergence: 5
## Achieved convergence tolerance: 5.842e-06
## (15 observations deleted due to missingness)summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 139 82.744
## 2 138 82.744 1 0.00 0.0000 0.99993
## 3 124 69.784 14 12.96 1.6449 0.07618 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3 1424.171
## 2 4 1550.105
## 3 5 1552.105
## 4 6 1417.784##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.248671 2.581509 0.484 0.6295
## phi 0.008552 0.039876 0.214 0.8305
## alpha 1.051526 0.227710 4.618 9.55e-06 ***
## a 27.252918 15.017274 1.815 0.0720 .
## b 51.099738 25.812648 1.980 0.0500 *
## c 89.540809 37.711187 2.374 0.0191 *
## d 0.908423 0.492970 1.843 0.0678 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7502 on 124 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (15 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.87531, p-value = 4.194e-09
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -3.4376, p-value = 0.0005869
## alternative hypothesis: two.sidedpredict and plot
plotting 2
341 - Nevada-Utah Mountains Semi-Desert - Coniferous Forest - Alpine Meadow
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"- model not fitted because only 62 observations
predict and plot
## [1] "cannot plot data with prediction"plotting 2
## [1] "cannot plot observed vs. predicted"342 - Intermountain Semi-Desert
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
## [1] "cannot plot observed vs. predicted"411 - Everglades
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
## [1] "cannot plot observed vs. predicted"M211 - Adirondack-New England Mixed forest - Coniferous Forest - Alpine Meadow
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 3966 645.80
## 2 3965 639.67 1 6.126 37.974 7.886e-10 ***
## 3 3951 603.74 14 35.932 16.797 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 42166.19
## 2 2 42130.36
## 3 3 41805.10##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 9.470e-01 2.122e-01 4.464 8.28e-06 ***
## phi 2.770e-02 4.662e-03 5.941 3.08e-09 ***
## alpha 8.963e-01 6.595e-02 13.590 < 2e-16 ***
## A 3.697e+02 2.607e+01 14.178 < 2e-16 ***
## k 1.712e+02 1.239e+01 13.812 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3909 on 3951 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 8.688e-06
## (14 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Error in numericDeriv(form[[3L]], names(ind), env, central = nDcentral) :
## Missing value or an infinity produced when evaluating the model
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 3951 603.74
## 2 3950 600.51 1 3.2239 21.206 4.255e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3 41805.10
## 2 3a 41785.92
## 3 3b 41770.56
## 4 3c NA##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (A * STDAGE_t2^s/(k^s +
## STDAGE_t2^s))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 8.376e-01 2.028e-01 4.129 3.71e-05 ***
## phi 2.518e-02 4.623e-03 5.446 5.46e-08 ***
## alpha 9.234e-01 6.631e-02 13.924 < 2e-16 ***
## A 2.166e+02 1.626e+01 13.321 < 2e-16 ***
## k 6.557e+01 6.665e+00 9.838 < 2e-16 ***
## s 1.361e+00 6.647e-02 20.472 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3892 on 3950 degrees of freedom
##
## Number of iterations to convergence: 5
## Achieved convergence tolerance: 2.404e-06
## (14 observations deleted due to missingness)summary
- add p model: fits
- add s model: fits
- add s+p model: does not fit
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 3964 637.04
## 2 3963 631.93 1 5.106 32.02 1.633e-08 ***
## 3 3949 595.38 14 36.557 17.32 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3b 41770.56
## 2 4 42116.02
## 3 5 42086.08
## 4 6 41753.95##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 9.106e-01 2.093e-01 4.351 1.39e-05 ***
## phi 2.481e-02 4.607e-03 5.385 7.67e-08 ***
## alpha 9.317e-01 6.524e-02 14.281 < 2e-16 ***
## a 2.114e+01 2.911e+00 7.262 4.58e-13 ***
## b 1.292e+02 8.907e+00 14.504 < 2e-16 ***
## c 1.595e+02 1.517e+01 10.520 < 2e-16 ***
## d 1.410e+00 9.726e-02 14.501 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3883 on 3949 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (14 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.98857, p-value < 2.2e-16
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -25.522, p-value < 2.2e-16
## alternative hypothesis: two.sidedpredict and plot
plotting 2
M221 - Eastern Broadleaf Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 4620 758.87
## 2 4619 752.69 1 6.181 37.9323 7.946e-10 ***
## 3 4592 713.21 27 39.481 9.4149 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 51198.35
## 2 2 51162.54
## 3 3 50693.40##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.186629 0.178040 6.665 2.96e-11 ***
## phi -0.030766 0.004769 -6.451 1.22e-10 ***
## alpha 0.912149 0.061890 14.738 < 2e-16 ***
## A 242.040492 10.235079 23.648 < 2e-16 ***
## k 58.152174 3.131309 18.571 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3941 on 4592 degrees of freedom
##
## Number of iterations to convergence: 5
## Achieved convergence tolerance: 7.32e-06
## (27 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (A * STDAGE_t2^s/(k^s + STDAGE_t2^s))
## Model 4: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2^s/(k^s + STDAGE_t2^s)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 4592 713.21
## 2 4591 712.39 1 0.8188 5.2765 0.02166 *
## 3 4591 708.03 0 0.0000
## 4 4590 696.82 1 11.2058 73.8132 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3 50693.40
## 2 3a 50690.12
## 3 3b 50661.89
## 4 3c 50590.55##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) *
## A * STDAGE_t2^s/(k^s + STDAGE_t2^s)))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.382841 0.189176 7.310 3.14e-13 ***
## phi -0.030859 0.004698 -6.568 5.65e-11 ***
## alpha 0.921594 0.060174 15.316 < 2e-16 ***
## A 149.863516 5.810322 25.793 < 2e-16 ***
## k 38.293455 1.124560 34.052 < 2e-16 ***
## p 0.247314 0.020701 11.947 < 2e-16 ***
## s 2.910487 0.241219 12.066 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3896 on 4590 degrees of freedom
##
## Number of iterations to convergence: 7
## Achieved convergence tolerance: 9.844e-06
## (27 observations deleted due to missingness)summary
- add p model: fits
- add s model: fits
- add s+p model: fits
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 4618 743.42
## 2 4617 743.42 1 0.000 0.000 1
## 3 4590 702.06 27 41.361 10.015 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3c 50590.55
## 2 4 51107.25
## 3 5 51109.25
## 4 6 50624.97##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) *
## A * STDAGE_t2^s/(k^s + STDAGE_t2^s)))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.382841 0.189176 7.310 3.14e-13 ***
## phi -0.030859 0.004698 -6.568 5.65e-11 ***
## alpha 0.921594 0.060174 15.316 < 2e-16 ***
## A 149.863516 5.810322 25.793 < 2e-16 ***
## k 38.293455 1.124560 34.052 < 2e-16 ***
## p 0.247314 0.020701 11.947 < 2e-16 ***
## s 2.910487 0.241219 12.066 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3896 on 4590 degrees of freedom
##
## Number of iterations to convergence: 7
## Achieved convergence tolerance: 9.844e-06
## (27 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.96958, p-value < 2.2e-16
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -25.3, p-value < 2.2e-16
## alternative hypothesis: two.sidedpredict and plot
plotting 2
M223 - Ozark Broadleaf Forest Meadow
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 523 64.694
## 2 522 62.454 1 2.2402 18.724 1.811e-05 ***
## 3 520 59.006 2 3.4479 15.193 3.868e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 5359.324
## 2 2 5342.787
## 3 3 5307.681##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.61595 0.24401 -2.524 0.011890 *
## phi 0.06602 0.01808 3.652 0.000286 ***
## alpha 0.89778 0.15614 5.750 1.52e-08 ***
## A 338.88585 50.01954 6.775 3.38e-11 ***
## k 100.37823 20.81388 4.823 1.86e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3369 on 520 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 9.662e-07
## (3 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Error in nls(get(paste("f_", Mod.Sel1, "c", sep = "")), data = G_M223, :
## number of iterations exceeded maximum of 50
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 520 59.006
## 2 519 58.894 1 0.11187 0.9859 0.3212
## model AIC
## 1 3 5307.681
## 2 3a 5308.684
## 3 3b 5309.018
## 4 3c NA##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.61595 0.24401 -2.524 0.011890 *
## phi 0.06602 0.01808 3.652 0.000286 ***
## alpha 0.89778 0.15614 5.750 1.52e-08 ***
## A 338.88585 50.01954 6.775 3.38e-11 ***
## k 100.37823 20.81388 4.823 1.86e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3369 on 520 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 9.662e-07
## (3 observations deleted due to missingness)summary
- add p model: fits
- add s model: fits
- add s+p model: does not fit
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 521 64.501
## 2 520 62.229 1 2.2721 18.986 1.587e-05 ***
## 3 518 58.912 2 3.3169 14.582 6.900e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3 5307.681
## 2 4 5361.749
## 3 5 5344.886
## 4 6 5310.841##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.61595 0.24401 -2.524 0.011890 *
## phi 0.06602 0.01808 3.652 0.000286 ***
## alpha 0.89778 0.15614 5.750 1.52e-08 ***
## A 338.88585 50.01954 6.775 3.38e-11 ***
## k 100.37823 20.81388 4.823 1.86e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3369 on 520 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 9.662e-07
## (3 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.96189, p-value = 2.028e-10
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -8.5579, p-value < 2.2e-16
## alternative hypothesis: two.sidedpredict and plot
plotting 2
M231 - Ouachita Mixed Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 586 115.11
## 2 585 115.11 1 0.0005 0.0027 0.9589
## 3 582 110.92 3 4.1918 7.3318 7.868e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 6079.429
## 2 2 6081.427
## 3 3 6047.977##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.572496 0.608073 0.941 0.346843
## phi -0.008085 0.017953 -0.450 0.652630
## alpha 0.882103 0.230491 3.827 0.000144 ***
## A 473.611228 148.437249 3.191 0.001496 **
## k 254.538269 86.216611 2.952 0.003281 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4366 on 582 degrees of freedom
##
## Number of iterations to convergence: 7
## Achieved convergence tolerance: 1.3e-06
## (3 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Error in numericDeriv(form[[3L]], names(ind), env, central = nDcentral) :
## Missing value or an infinity produced when evaluating the model
## Error in numericDeriv(form[[3L]], names(ind), env, central = nDcentral) :
## Missing value or an infinity produced when evaluating the model
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 582 110.92
## 2 581 110.62 1 0.2994 1.5726 0.2103
## model AIC
## 1 3 6047.977
## 2 3a 6048.391
## 3 3b 6915.692
## 4 3c NA##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.572496 0.608073 0.941 0.346843
## phi -0.008085 0.017953 -0.450 0.652630
## alpha 0.882103 0.230491 3.827 0.000144 ***
## A 473.611228 148.437249 3.191 0.001496 **
## k 254.538269 86.216611 2.952 0.003281 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4366 on 582 degrees of freedom
##
## Number of iterations to convergence: 7
## Achieved convergence tolerance: 1.3e-06
## (3 observations deleted due to missingness)summary
- add p model: fits
- add s model: fits
- add s+p model: does not fit
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 584 114.44
## 2 583 114.43 1 0.0054 0.0274 0.8685
## 3 580 110.29 3 4.1401 7.2574 8.728e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3 6047.977
## 2 4 6079.986
## 3 5 6081.958
## 4 6 6048.664##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.572496 0.608073 0.941 0.346843
## phi -0.008085 0.017953 -0.450 0.652630
## alpha 0.882103 0.230491 3.827 0.000144 ***
## A 473.611228 148.437249 3.191 0.001496 **
## k 254.538269 86.216611 2.952 0.003281 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4366 on 582 degrees of freedom
##
## Number of iterations to convergence: 7
## Achieved convergence tolerance: 1.3e-06
## (3 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.96323, p-value = 5.971e-11
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -9.5051, p-value < 2.2e-16
## alternative hypothesis: two.sidedpredict and plot
plotting 2
M242 - Cascade Mixed Forest
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
## [1] "cannot plot observed vs. predicted"M261 - Sierran Steppe - Mixed Forest - Coniferous Forest - Alpine Meadow
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 308 94.545
## 2 307 94.155 1 0.39 1.2728 0.2601
## 3 149 49.395 158 44.76 0.8545 0.8349
## model AIC
## 1 1 3309.570
## 2 2 3310.284
## 3 3 1658.712##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -1.43647 1.51047 -0.951 0.3431
## phi 0.02004 0.04933 0.406 0.6851
## alpha 0.74585 0.28704 2.598 0.0103 *
## A 193.80924 139.40676 1.390 0.1665
## k 12.32409 10.64052 1.158 0.2486
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5758 on 149 degrees of freedom
##
## Number of iterations to convergence: 10
## Achieved convergence tolerance: 7.773e-06
## (158 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Error in numericDeriv(form[[3L]], names(ind), env, central = nDcentral) :
## Missing value or an infinity produced when evaluating the model
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 149 49.395
## 2 148 49.191 1 0.20423 0.6145 0.4344
## model AIC
## 1 3 1658.712
## 2 3a 1660.074
## 3 3b 1648.175
## 4 3c NA##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (A * STDAGE_t2^s/(k^s +
## STDAGE_t2^s))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -1.626861 1.205601 -1.349 0.179
## phi 0.008848 0.048243 0.183 0.855
## alpha 0.587047 0.318116 1.845 0.067 .
## A 189.493730 117.280510 1.616 0.108
## k 40.017398 0.670930 59.645 <2e-16 ***
## s 63.679888 108.268749 0.588 0.557
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5547 on 148 degrees of freedom
##
## Number of iterations to convergence: 19
## Achieved convergence tolerance: 6.42e-06
## (158 observations deleted due to missingness)summary
- add p model: fits
- add s model: fits
- add s+p model: does not fit
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 306 91.857
## 2 305 91.040 1 0.818 2.7388 0.09897 .
## 3 147 47.591 158 43.449 0.8494 0.84325
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 3b 1648.175
## 2 4 3304.600
## 3 5 3303.820
## 4 6 1656.982##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * (A * STDAGE_t2^s/(k^s +
## STDAGE_t2^s))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -1.626861 1.205601 -1.349 0.179
## phi 0.008848 0.048243 0.183 0.855
## alpha 0.587047 0.318116 1.845 0.067 .
## A 189.493730 117.280510 1.616 0.108
## k 40.017398 0.670930 59.645 <2e-16 ***
## s 63.679888 108.268749 0.588 0.557
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5547 on 148 degrees of freedom
##
## Number of iterations to convergence: 19
## Achieved convergence tolerance: 6.42e-06
## (158 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.98431, p-value = 0.0781
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = 0.0021003, p-value = 0.9983
## alternative hypothesis: two.sidedpredict and plot
plotting 2
M262 - California coastal range - coniferous forest - open woodland - shrub meadow
Model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"- model can fit - but K is negative (only 19 observations) - model excluded
predict and plot
## [1] "cannot plot data with prediction"plotting 2
M313 - Arizona-New Mexico Mountains Semi-Desert - Open Woodland - Coniferous Forest - Alpine Meadow
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
M331 - Southern Rocky Mountain Steppe - Open Woodland - Coniferous Forest - Alpine Meadow
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
M332 - Middle Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
M333 - Northern Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
M334 - Black Hills Coniferous Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 247 102.693
## 2 246 102.569 1 0.1246 0.2990 0.5850
## 3 175 77.963 71 24.6053 0.7779 0.8865
## model AIC
## 1 1 2514.590
## 2 2 2516.287
## 3 3 1829.728##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.336427 1.519780 -0.221 0.82507
## phi -0.004472 0.040339 -0.111 0.91185
## alpha 0.772198 0.213500 3.617 0.00039 ***
## A 110.544511 48.539478 2.277 0.02397 *
## k 50.619975 25.176162 2.011 0.04590 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6675 on 175 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 5.61e-06
## (74 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
model selection 2
## Error in nls(get(paste("f_", Mod.Sel1, "a", sep = "")), data = G_M334, :
## number of iterations exceeded maximum of 50
## Error in nls(get(paste("f_", Mod.Sel1, "c", sep = "")), data = G_M334, :
## number of iterations exceeded maximum of 50
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k + STDAGE_t2)
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2/(k + STDAGE_t2)))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (A * STDAGE_t2^s/(k^s + STDAGE_t2^s))
## Model 4: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (p * A + ((1 - p) * A * STDAGE_t2^s/(k^s + STDAGE_t2^s)))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 175 77.963
## 2 211 86.584 -36 -8.6205 0.5375 0.9851
## 3 174 77.438 37 9.1463 0.5554 0.9817
## 4 210 86.173 -36 -8.7353 0.5452 0.9832
## model AIC
## 1 3 1829.728
## 2 3a 2170.479
## 3 3b 1830.510
## 4 3c 2171.446##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.336427 1.519780 -0.221 0.82507
## phi -0.004472 0.040339 -0.111 0.91185
## alpha 0.772198 0.213500 3.617 0.00039 ***
## A 110.544511 48.539478 2.277 0.02397 *
## k 50.619975 25.176162 2.011 0.04590 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6675 on 175 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 5.61e-06
## (74 observations deleted due to missingness)summary
- add p model: fits
- add s model: fits
- add s+p model: fits
model selection 3
## Analysis of Variance Table
##
## Model 1: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 2: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Model 3: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t2/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 245 102.324
## 2 244 102.324 1 0.00 0.0000 1.0000
## 3 173 77.733 71 24.59 0.7708 0.8945
## model AIC
## 1 3 1829.728
## 2 4 2517.688
## 3 5 2519.688
## 4 6 1833.196##
## Formula: B_plt_t2_MgHa ~ (1 + (MEASTIME_t2 - 1990) * ge/100) * (1 + phi *
## DeltaPDSI) * (1 - alpha * B_L_prop) * A * STDAGE_t2/(k +
## STDAGE_t2)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.336427 1.519780 -0.221 0.82507
## phi -0.004472 0.040339 -0.111 0.91185
## alpha 0.772198 0.213500 3.617 0.00039 ***
## A 110.544511 48.539478 2.277 0.02397 *
## k 50.619975 25.176162 2.011 0.04590 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6675 on 175 degrees of freedom
##
## Number of iterations to convergence: 6
## Achieved convergence tolerance: 5.61e-06
## (74 observations deleted due to missingness)summary
- simple log-normal model: fits
- log-normal phi model: fits
- log-normal phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.93026, p-value = 1.295e-07
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -3.5617, p-value = 0.0003684
## alternative hypothesis: two.sidedpredict and plot
plotting 2
M341 - Nevada-Utah Mountains Semi-Desert - Coniferous Forest - Alpine Meadow
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
model selection 2
summary
- add p model: does not fit
- add s model: does not fit
- add s+p model: does not fit
model selection 3
summary
- simple log-normal model: does not fit
- log-normal phi model: does not fit
- log-normal phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
Fitted parameters
Best / selected models by ecoprovince
| Code | Ecoregion | Sel.Mod.2 | Sel.Mod.3 | Best.Mod |
|---|---|---|---|---|
| 211 | Northeastern Mixed Forest | 3b | 6 | 6 |
| 212 | Laurentian Mixed Forest | 3c | 6 | 6 |
| 221 | Eastern Broadleaf Forest | 3b | 6 | 6 |
| 222 | Midwest Broadleaf Forest | 3a | 6 | 6 |
| 223 | Central Interior Broadleaf Forest | 3b | 6 | 6 |
| 231 | Southeastern Mixed Forest | 3c | 6 | 6 |
| 232 | Outer Coastal Plain Mixed Forest | 3c | 6 | 6 |
| 234 | Lower Mississippi Riverine Forest | 3 | 3 | 3 |
| 242 | Pacific Lowland Mixed Forest | NA | NA | NA |
| 251 | Prairie Parkland (Temperate) | 3b | 6 | 6 |
| 255 | Prairie Parkland (Subtropical) | 3a | 6 | 6 |
| 261 | California Coastal Chaparral Forest and Shrub | NA | NA | NA |
| 262 | California Dry Steppe | NA | NA | NA |
| 263 | California Coastal Steppe - Mixed Forest and Redwood Forest | NA | NA | NA |
| 313 | Colorado Plateau Semi-Desert | NA | NA | NA |
| 315 | Southwest Plateau and Plains Dry Steppe and Shrub | NA | NA | NA |
| 321 | Chihuahuan Semi-Desert | NA | NA | NA |
| 322 | American Semidesert and Desert | NA | NA | NA |
| 331 | Great Plains/Palouse Dry Steppe | NA | NA | NA |
| 332 | Great Plains Steppe | 3 | 6 | 6 |
| 341 | Intermountain Semi-Desert and Desert | NA | NA | NA |
| 342 | Intermountain Semi-Desert | NA | NA | NA |
| 411 | Everglades | NA | NA | NA |
| M211 | Adirondack-New England Mixed forest - Coniferous Forest - Alpine Meadow | 3b | 6 | 6 |
| M221 | Central Appalachian Broadleaf Forest - Coniferous Forest - Meadow | 3c | 3c | 3c |
| M223 | Ozark Broadleaf Forest Meadow | 3 | 3 | 3 |
| M231 | Ouachita Mixed Forest | 3 | 3 | 3 |
| M242 | Cascade Mixed Forest | NA | NA | NA |
| M261 | Sierran Steppe - Mixed Forest - Coniferous Forest - Alpine Meadow | 3b | 3b | 3b |
| M262 | California Coastal Range Coniferous Forest - Open Woodland - Shrub - Meadow | NA | NA | NA |
| M313 | Arizona-New Mexico Mountains Semi-Desert - Open Woodland - Coniferous Forest - Alpine Meadow | NA | NA | NA |
| M331 | Southern Rocky Mountain Steppe - Open Woodland - Coniferous Forest - Alpine Meadow | NA | NA | NA |
| M332 | Middle Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow | NA | NA | NA |
| M333 | Northern Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow | NA | NA | NA |
| M334 | Black Hills Coniferous Forest | 3 | 3 | 3 |
| M341 | Nevada-Utah Mountains Semi-Desert - Coniferous Forest - Alpine Meadow | NA | NA | NA |
table by ecoprovince
| Code | Ecoregion | region | n.obs | n.plots | ge | ge.variance | ge.2.5 | ge.97.5 | phi | phi.variance | phi.2.5 | phi.97.5 | alpha | alpha.variance | alpha.2.5 | alpha.97.5 | A | A.2.5 | A.97.5 | k | k.2.5 | k.97.5 | a | a.2.5 | a.97.5 | b | b.se | b.2.5 | b.97.5 | c | c.2.5 | c.97.5 | d | d.2.5 | d.97.5 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 211 | Northeastern Mixed Forest | east | 4838 | 2419 | 0.6301633 | 0.0478700 | 0.2011991 | 1.0591274 | 0.0169332 | 0.0000322 | 0.0058101 | 0.0280563 | 1.1697903 | 0.0046962 | 1.0354324 | 1.3041482 | 313.9973 | 224.90265 | 403.0919 | 103.10784 | 57.3911644 | 148.82451 | 38.93749 | 34.564842 | 43.31014 | 112.24482 | NA | 99.8673859 | 124.62226 | 116.17018 | 104.95394 | 127.38642 | 0.9314725 | 0.8278628 | 1.035082 |
| 212 | Laurentian Mixed Forest | east | 12962 | 6481 | 0.1808888 | 0.0234806 | -0.1194899 | 0.4812674 | 0.0211932 | 0.0000203 | 0.0123708 | 0.0300155 | 0.9083255 | 0.0018663 | 0.8236415 | 0.9930094 | 124.8983 | 112.63007 | 137.1665 | 45.82483 | 41.9172456 | 49.73240 | 23.57869 | 21.015035 | 26.14235 | 86.44570 | NA | 78.8333156 | 94.05809 | 125.36219 | 111.21370 | 139.51068 | 1.3509549 | 1.2283128 | 1.473597 |
| 221 | Eastern Broadleaf Forest | east | 5446 | 2723 | 0.6042574 | 0.0295961 | 0.2669821 | 0.9415327 | 0.0000000 | 0.0000197 | -0.0086968 | 0.0086968 | 0.9247621 | 0.0026719 | 0.8234238 | 1.0261003 | 269.2999 | 226.45981 | 312.1400 | 61.79384 | 48.5722847 | 75.01539 | 27.90799 | 21.840874 | 33.97510 | 151.78054 | NA | 134.6780153 | 168.88306 | 133.03954 | 112.19473 | 153.88434 | 1.3181621 | 1.1569422 | 1.479382 |
| 222 | Midwest Broadleaf Forest | east | 3552 | 1776 | -0.3019439 | 0.0650521 | -0.8021219 | 0.1982342 | 0.0457054 | 0.0001683 | 0.0202607 | 0.0711502 | 0.9776442 | 0.0055842 | 0.8310980 | 1.1241904 | 415.2918 | 291.42919 | 539.1544 | 145.60494 | 82.6853980 | 208.52448 | 25.34285 | 20.338823 | 30.34688 | 125.49277 | NA | 107.9061657 | 143.07938 | 105.73419 | 91.72965 | 119.73874 | 1.0355867 | 0.8961121 | 1.175061 |
| 223 | Central Interior Broadleaf Forest | east | 6388 | 3194 | -0.0887126 | 0.0180864 | -0.3523746 | 0.1749494 | 0.0000000 | 0.0000392 | -0.0122715 | 0.0122715 | 0.8518000 | 0.0031221 | 0.7422544 | 0.9613455 | 187.6025 | 165.85945 | 209.3455 | 40.38205 | 34.4914196 | 46.27268 | 29.94935 | 24.307638 | 35.59107 | 116.92794 | NA | 106.3505886 | 127.50530 | 104.05768 | 92.83703 | 115.27834 | 1.2094471 | 1.0687829 | 1.350111 |
| 231 | Southeastern Mixed Forest | east | 7790 | 3895 | 1.5684019 | 0.0344772 | 1.2044010 | 1.9324028 | 0.0000000 | 0.0000216 | -0.0091043 | 0.0091043 | 0.8342246 | 0.0021963 | 0.7423523 | 0.9260969 | 159.4438 | 142.63460 | 176.2530 | 34.73307 | 30.9341582 | 38.53197 | 16.88756 | 13.676656 | 20.09847 | 127.95402 | NA | 112.9401111 | 142.96793 | 137.97548 | 105.68394 | 170.26702 | 1.7878677 | 1.5849700 | 1.990765 |
| 232 | Outer Coastal Plain Mixed Forest | east | 7940 | 3970 | 1.0398178 | 0.0414701 | 0.6406081 | 1.4390274 | 0.0109689 | 0.0000289 | 0.0004379 | 0.0215000 | 0.8062593 | 0.0019510 | 0.7196702 | 0.8928484 | 161.5742 | 142.76226 | 180.3861 | 36.06069 | 31.9700715 | 40.15132 | 21.48141 | 17.892126 | 25.07070 | 129.35806 | NA | 112.0857189 | 146.63040 | 136.70672 | 102.42869 | 170.98475 | 1.6721462 | 1.4578732 | 1.886419 |
| 234 | Lower Mississippi Riverine Forest | east | 830 | 415 | 0.0548083 | 0.2309309 | -0.8888094 | 0.9984260 | 0.0265263 | 0.0003264 | -0.0089483 | 0.0620009 | 0.8914939 | 0.0107605 | 0.6878037 | 1.0951842 | 622.1739 | 329.30518 | 915.0427 | 187.66098 | 86.9903041 | 288.33166 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 242 | Pacific Lowland Mixed Forest | pacific | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 251 | Prairie Parkland (Temperate) | east | 1392 | 696 | 0.5935419 | 0.2163450 | -0.3193746 | 1.5064584 | 0.0000000 | 0.0001373 | -0.0230016 | 0.0230016 | 0.7683654 | 0.0127436 | 0.5467994 | 0.9899313 | 151.4269 | 102.96746 | 199.8864 | 45.36071 | 27.6437845 | 63.07764 | 24.43593 | 10.347990 | 38.52387 | 91.93815 | NA | 65.9754728 | 117.90083 | 114.37086 | 80.22754 | 148.51418 | 1.2279330 | 0.8354607 | 1.620405 |
| 255 | Prairie Parkland (Subtropical) | east | 444 | 222 | -0.3921693 | 0.2317805 | -1.3387733 | 0.5544348 | 0.0000000 | 0.0004578 | -0.0420678 | 0.0420678 | 0.6719871 | 0.0210045 | 0.3870259 | 0.9569483 | 285.1230 | 27.58813 | 542.6580 | 127.22908 | -47.0746672 | 301.53282 | 24.37674 | 17.325824 | 31.42766 | 78.28675 | NA | 56.8429742 | 99.73053 | 56.06386 | 43.93946 | 68.18827 | 0.9505804 | 0.6808014 | 1.220360 |
| 261 | California Coastal Chaparral Forest and Shrub | pacific | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 262 | California Dry Steppe | pacific | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 263 | California Coastal Steppe - Mixed Forest and Redwood Forest | pacific | 4 | 2 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 313 | Colorado Plateau Semi-Desert | interior west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 315 | Southwest Plateau and Plains Dry Steppe and Shrub | interior west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 321 | Chihuahuan Semi-Desert | interior west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 322 | American Semidesert and Desert | interior west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 331 | Great Plains/Palouse Dry Steppe | interior west | 118 | 59 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 332 | Great Plains Steppe | interior west | 154 | 77 | 1.2486710 | 6.6641900 | -3.8608589 | 6.3582010 | 0.0085525 | 0.0015901 | -0.0703735 | 0.0874784 | 1.0515265 | 0.0518519 | 0.6008244 | 1.5022286 | 182.1294 | -28.01655 | 392.2753 | 85.27547 | -28.4217543 | 198.97270 | 27.25292 | -2.470473 | 56.97631 | 51.09974 | NA | 0.0092781 | 102.19020 | 89.54081 | 14.89981 | 164.18181 | 0.9084226 | -0.0673038 | 1.884149 |
| 341 | Intermountain Semi-Desert and Desert | interior west | 4 | 2 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 342 | Intermountain Semi-Desert | interior west | 2 | 1 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 411 | Everglades | east | 66 | 33 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M211 | Adirondack-New England Mixed forest - Coniferous Forest - Alpine Meadow | east | 5108 | 2554 | 0.9106063 | 0.0437947 | 0.5003152 | 1.3208974 | 0.0248077 | 0.0000212 | 0.0157755 | 0.0338399 | 0.9317467 | 0.0042567 | 0.8038335 | 1.0596599 | 216.5856 | 184.70893 | 248.4623 | 65.57398 | 52.5065750 | 78.64139 | 21.13968 | 15.432210 | 26.84715 | 129.19346 | NA | 111.7300914 | 146.65682 | 159.54583 | 129.81340 | 189.27826 | 1.4103995 | 1.2197164 | 1.601082 |
| M221 | Central Appalachian Broadleaf Forest - Coniferous Forest - Meadow | east | 5186 | 2593 | 1.3828406 | 0.0357875 | 1.0119648 | 1.7537165 | -0.0308590 | 0.0000221 | -0.0400697 | -0.0216484 | 0.9215941 | 0.0036209 | 0.8036248 | 1.0395634 | 149.8635 | 138.47249 | 161.2545 | 38.29346 | 36.0887776 | 40.49813 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M223 | Ozark Broadleaf Forest Meadow | east | 602 | 301 | -0.6159480 | 0.0595402 | -1.0953117 | -0.1365842 | 0.0660238 | 0.0003268 | 0.0305091 | 0.1015385 | 0.8977772 | 0.0243786 | 0.5910414 | 1.2045130 | 338.8858 | 240.62063 | 437.1511 | 100.37823 | 59.4885909 | 141.26786 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M231 | Ouachita Mixed Forest | east | 680 | 340 | 0.5724965 | 0.3697528 | -0.6217884 | 1.7667813 | -0.0080849 | 0.0003223 | -0.0433450 | 0.0271752 | 0.8821030 | 0.0531259 | 0.4294083 | 1.3347977 | 473.6112 | 182.07329 | 765.1492 | 254.53827 | 85.2046721 | 423.87187 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M242 | Cascade Mixed Forest | pacific | 34 | 17 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M261 | Sierran Steppe - Mixed Forest - Coniferous Forest - Alpine Meadow | pacific | 330 | 165 | -1.6268614 | 1.4534734 | -4.0092764 | 0.7555535 | 0.0088479 | 0.0023274 | -0.0864860 | 0.1041818 | 0.5870475 | 0.1011980 | -0.0415895 | 1.2156844 | 189.4937 | -42.26693 | 421.2544 | 40.01740 | 38.6915584 | 41.34324 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M262 | California Coastal Range Coniferous Forest - Open Woodland - Shrub - Meadow | interior west | 8 | 4 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M313 | Arizona-New Mexico Mountains Semi-Desert - Open Woodland - Coniferous Forest - Alpine Meadow | interior west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M331 | Southern Rocky Mountain Steppe - Open Woodland - Coniferous Forest - Alpine Meadow | interior west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M332 | Middle Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow | interior west | 20 | 10 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M333 | Northern Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow | interior west | 22 | 11 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M334 | Black Hills Coniferous Forest | interior west | 306 | 153 | -0.3364271 | 2.3097314 | -3.3358839 | 2.6630297 | -0.0044724 | 0.0016272 | -0.0840860 | 0.0751412 | 0.7721982 | 0.0455825 | 0.3508309 | 1.1935654 | 110.5445 | 14.74639 | 206.3426 | 50.61997 | 0.9319872 | 100.30796 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M341 | Nevada-Utah Mountains Semi-Desert - Coniferous Forest - Alpine Meadow | interior west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
plot ge
map
## OGR data source with driver: ESRI Shapefile
## Source: "C:\Users\hogan.jaaron\Dropbox\FIA_R\Mapping\S_USA.EcoMapProvinces\S_USA.EcoMapProvinces.shp", layer: "S_USA.EcoMapProvinces"
## with 37 features
## It has 17 fields
## Integer64 fields read as strings: PROVINCE_ PROVINCE_I
plot phi (effect of DeltaPDSI)
plot alpha (biomass compensation effect)
plot A (asymptote of B)
## Warning: Removed 19 rows containing missing values (geom_point).
plot k (stand age at half biomass asymptote)
## Warning: Removed 19 rows containing missing values (geom_point).
Caclulations - weighted averages
ge (stand biomass enhancement factor in % 2000-2021)
## region weighted.ge weighted.ge.std_Error 95 % CI, upper
## 1 entire US 0.616733834 0.061620764 0.737510532
## 2 pacific -0.008358986 0.006194505 0.003782243
## 3 east 0.623701660 0.060564028 0.742407156
## 4 interior west 0.001391160 0.009526026 0.020062171
## 95 % CI, lower
## 1 0.49595714
## 2 -0.02050022
## 3 0.50499617
## 4 -0.01727985phi (effect of DeltaPDSI)
## region weighted.phi weighted.phi.std_Error 95 % CI, upper
## 1 entire US 9.838444e-03 5.743138e-08 9.838557e-03
## 2 pacific 4.546141e-05 7.718904e-09 4.547654e-05
## 3 east 9.793784e-03 5.651635e-08 9.793895e-03
## 4 interior west -8.014508e-07 6.684597e-09 -7.883490e-07
## 95 % CI, lower
## 1 9.838332e-03
## 2 4.544628e-05
## 3 9.793674e-03
## 4 -8.145526e-07alpha (biomass compensation effect)
## region weighted.alpha weighted.alpha.std_Error 95 % CI, upper
## 1 entire US 0.897805788 5.423982e-07 0.897806851
## 2 pacific 0.003016312 5.089888e-08 0.003016412
## 3 east 0.888589063 5.388067e-07 0.888590119
## 4 interior west 0.006200413 3.595057e-08 0.006200483
## 95 % CI, lower
## 1 0.897804725
## 2 0.003016212
## 3 0.888588007
## 4 0.006200342A (asymptote of forest biomass in Mg/ha)
## region weighted.A
## 1 entire US 205.3828
## 2 pacific 169.9264
## 3 east 206.6700
## 4 interior west 0.0000K (stand age at half maturation in years)
## region weighted.k
## 1 entire US 59.87703
## 2 pacific 35.88517
## 3 east 60.16440
## 4 interior west 45.14532Model Bookeeping
1. Delta-B due to Delta-STDAGE
2. Delta-B due to Delta-Year (ge)
make a fig
## Warning: Removed 10138 rows containing missing values (geom_point).
3. stand age densities
make a fig
## Picking joint bandwidth of 7.36
